YOLOv3-CoreML
YOLOv3-CoreML copied to clipboard
Published
20 hours ago •
Ma-Dan
Ma-Dan
Convert to h5 is fine, but failed to further convert to coreml model
By following the description of keras-yolo3, I converted yolov3.weights to keras model yolo.h5. However, the conversion from yolo.h5 to its CoreML model failed. I pasted the detailed command line output as below. The error message and my environment details can be found in the bottom of this post. Sorry for the long command line output.
- convert yolov3.weights to keras model yolo.h5
$ python convert.py yolov3.cfg yolov3.weights model_data/yolo.h5
Using TensorFlow backend.
Loading weights.
Weights Header: 0 2 0 [32013312]
Parsing Darknet config.
Creating Keras model.
Parsing section net_0
Parsing section convolutional_0
conv2d bn leaky (3, 3, 3, 32)
2018-06-18 10:02:53.364525: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Parsing section convolutional_1
conv2d bn leaky (3, 3, 32, 64)
Parsing section convolutional_2
conv2d bn leaky (1, 1, 64, 32)
Parsing section convolutional_3
conv2d bn leaky (3, 3, 32, 64)
Parsing section shortcut_0
Parsing section convolutional_4
conv2d bn leaky (3, 3, 64, 128)
Parsing section convolutional_5
conv2d bn leaky (1, 1, 128, 64)
Parsing section convolutional_6
conv2d bn leaky (3, 3, 64, 128)
Parsing section shortcut_1
Parsing section convolutional_7
conv2d bn leaky (1, 1, 128, 64)
Parsing section convolutional_8
conv2d bn leaky (3, 3, 64, 128)
Parsing section shortcut_2
Parsing section convolutional_9
conv2d bn leaky (3, 3, 128, 256)
Parsing section convolutional_10
conv2d bn leaky (1, 1, 256, 128)
Parsing section convolutional_11
conv2d bn leaky (3, 3, 128, 256)
Parsing section shortcut_3
Parsing section convolutional_12
conv2d bn leaky (1, 1, 256, 128)
Parsing section convolutional_13
conv2d bn leaky (3, 3, 128, 256)
Parsing section shortcut_4
Parsing section convolutional_14
conv2d bn leaky (1, 1, 256, 128)
Parsing section convolutional_15
conv2d bn leaky (3, 3, 128, 256)
Parsing section shortcut_5
Parsing section convolutional_16
conv2d bn leaky (1, 1, 256, 128)
Parsing section convolutional_17
conv2d bn leaky (3, 3, 128, 256)
Parsing section shortcut_6
Parsing section convolutional_18
conv2d bn leaky (1, 1, 256, 128)
Parsing section convolutional_19
conv2d bn leaky (3, 3, 128, 256)
Parsing section shortcut_7
Parsing section convolutional_20
conv2d bn leaky (1, 1, 256, 128)
Parsing section convolutional_21
conv2d bn leaky (3, 3, 128, 256)
Parsing section shortcut_8
Parsing section convolutional_22
conv2d bn leaky (1, 1, 256, 128)
Parsing section convolutional_23
conv2d bn leaky (3, 3, 128, 256)
Parsing section shortcut_9
Parsing section convolutional_24
conv2d bn leaky (1, 1, 256, 128)
Parsing section convolutional_25
conv2d bn leaky (3, 3, 128, 256)
Parsing section shortcut_10
Parsing section convolutional_26
conv2d bn leaky (3, 3, 256, 512)
Parsing section convolutional_27
conv2d bn leaky (1, 1, 512, 256)
Parsing section convolutional_28
conv2d bn leaky (3, 3, 256, 512)
Parsing section shortcut_11
Parsing section convolutional_29
conv2d bn leaky (1, 1, 512, 256)
Parsing section convolutional_30
conv2d bn leaky (3, 3, 256, 512)
Parsing section shortcut_12
Parsing section convolutional_31
conv2d bn leaky (1, 1, 512, 256)
Parsing section convolutional_32
conv2d bn leaky (3, 3, 256, 512)
Parsing section shortcut_13
Parsing section convolutional_33
conv2d bn leaky (1, 1, 512, 256)
Parsing section convolutional_34
conv2d bn leaky (3, 3, 256, 512)
Parsing section shortcut_14
Parsing section convolutional_35
conv2d bn leaky (1, 1, 512, 256)
Parsing section convolutional_36
conv2d bn leaky (3, 3, 256, 512)
Parsing section shortcut_15
Parsing section convolutional_37
conv2d bn leaky (1, 1, 512, 256)
Parsing section convolutional_38
conv2d bn leaky (3, 3, 256, 512)
Parsing section shortcut_16
Parsing section convolutional_39
conv2d bn leaky (1, 1, 512, 256)
Parsing section convolutional_40
conv2d bn leaky (3, 3, 256, 512)
Parsing section shortcut_17
Parsing section convolutional_41
conv2d bn leaky (1, 1, 512, 256)
Parsing section convolutional_42
conv2d bn leaky (3, 3, 256, 512)
Parsing section shortcut_18
Parsing section convolutional_43
conv2d bn leaky (3, 3, 512, 1024)
Parsing section convolutional_44
conv2d bn leaky (1, 1, 1024, 512)
Parsing section convolutional_45
conv2d bn leaky (3, 3, 512, 1024)
Parsing section shortcut_19
Parsing section convolutional_46
conv2d bn leaky (1, 1, 1024, 512)
Parsing section convolutional_47
conv2d bn leaky (3, 3, 512, 1024)
Parsing section shortcut_20
Parsing section convolutional_48
conv2d bn leaky (1, 1, 1024, 512)
Parsing section convolutional_49
conv2d bn leaky (3, 3, 512, 1024)
Parsing section shortcut_21
Parsing section convolutional_50
conv2d bn leaky (1, 1, 1024, 512)
Parsing section convolutional_51
conv2d bn leaky (3, 3, 512, 1024)
Parsing section shortcut_22
Parsing section convolutional_52
conv2d bn leaky (1, 1, 1024, 512)
Parsing section convolutional_53
conv2d bn leaky (3, 3, 512, 1024)
Parsing section convolutional_54
conv2d bn leaky (1, 1, 1024, 512)
Parsing section convolutional_55
conv2d bn leaky (3, 3, 512, 1024)
Parsing section convolutional_56
conv2d bn leaky (1, 1, 1024, 512)
Parsing section convolutional_57
conv2d bn leaky (3, 3, 512, 1024)
Parsing section convolutional_58
conv2d linear (1, 1, 1024, 255)
Parsing section yolo_0
Parsing section route_0
Parsing section convolutional_59
conv2d bn leaky (1, 1, 512, 256)
Parsing section upsample_0
Parsing section route_1
Concatenating route layers: [<tf.Tensor 'up_sampling2d_1/ResizeNearestNeighbor:0' shape=(?, ?, ?, 256) dtype=float32>, <tf.Tensor 'add_19/add:0' shape=(?, ?, ?, 512) dtype=float32>]
Parsing section convolutional_60
conv2d bn leaky (1, 1, 768, 256)
Parsing section convolutional_61
conv2d bn leaky (3, 3, 256, 512)
Parsing section convolutional_62
conv2d bn leaky (1, 1, 512, 256)
Parsing section convolutional_63
conv2d bn leaky (3, 3, 256, 512)
Parsing section convolutional_64
conv2d bn leaky (1, 1, 512, 256)
Parsing section convolutional_65
conv2d bn leaky (3, 3, 256, 512)
Parsing section convolutional_66
conv2d linear (1, 1, 512, 255)
Parsing section yolo_1
Parsing section route_2
Parsing section convolutional_67
conv2d bn leaky (1, 1, 256, 128)
Parsing section upsample_1
Parsing section route_3
Concatenating route layers: [<tf.Tensor 'up_sampling2d_2/ResizeNearestNeighbor:0' shape=(?, ?, ?, 128) dtype=float32>, <tf.Tensor 'add_11/add:0' shape=(?, ?, ?, 256) dtype=float32>]
Parsing section convolutional_68
conv2d bn leaky (1, 1, 384, 128)
Parsing section convolutional_69
conv2d bn leaky (3, 3, 128, 256)
Parsing section convolutional_70
conv2d bn leaky (1, 1, 256, 128)
Parsing section convolutional_71
conv2d bn leaky (3, 3, 128, 256)
Parsing section convolutional_72
conv2d bn leaky (1, 1, 256, 128)
Parsing section convolutional_73
conv2d bn leaky (3, 3, 128, 256)
Parsing section convolutional_74
conv2d linear (1, 1, 256, 255)
Parsing section yolo_2
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) (None, None, None, 3 0
__________________________________________________________________________________________________
conv2d_1 (Conv2D) (None, None, None, 3 864 input_1[0][0]
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, None, None, 3 128 conv2d_1[0][0]
__________________________________________________________________________________________________
leaky_re_lu_1 (LeakyReLU) (None, None, None, 3 0 batch_normalization_1[0][0]
__________________________________________________________________________________________________
zero_padding2d_1 (ZeroPadding2D (None, None, None, 3 0 leaky_re_lu_1[0][0]
__________________________________________________________________________________________________
conv2d_2 (Conv2D) (None, None, None, 6 18432 zero_padding2d_1[0][0]
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, None, None, 6 256 conv2d_2[0][0]
__________________________________________________________________________________________________
leaky_re_lu_2 (LeakyReLU) (None, None, None, 6 0 batch_normalization_2[0][0]
__________________________________________________________________________________________________
conv2d_3 (Conv2D) (None, None, None, 3 2048 leaky_re_lu_2[0][0]
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, None, None, 3 128 conv2d_3[0][0]
__________________________________________________________________________________________________
leaky_re_lu_3 (LeakyReLU) (None, None, None, 3 0 batch_normalization_3[0][0]
__________________________________________________________________________________________________
conv2d_4 (Conv2D) (None, None, None, 6 18432 leaky_re_lu_3[0][0]
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, None, None, 6 256 conv2d_4[0][0]
__________________________________________________________________________________________________
leaky_re_lu_4 (LeakyReLU) (None, None, None, 6 0 batch_normalization_4[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, None, None, 6 0 leaky_re_lu_2[0][0]
leaky_re_lu_4[0][0]
__________________________________________________________________________________________________
zero_padding2d_2 (ZeroPadding2D (None, None, None, 6 0 add_1[0][0]
__________________________________________________________________________________________________
conv2d_5 (Conv2D) (None, None, None, 1 73728 zero_padding2d_2[0][0]
__________________________________________________________________________________________________
batch_normalization_5 (BatchNor (None, None, None, 1 512 conv2d_5[0][0]
__________________________________________________________________________________________________
leaky_re_lu_5 (LeakyReLU) (None, None, None, 1 0 batch_normalization_5[0][0]
__________________________________________________________________________________________________
conv2d_6 (Conv2D) (None, None, None, 6 8192 leaky_re_lu_5[0][0]
__________________________________________________________________________________________________
batch_normalization_6 (BatchNor (None, None, None, 6 256 conv2d_6[0][0]
__________________________________________________________________________________________________
leaky_re_lu_6 (LeakyReLU) (None, None, None, 6 0 batch_normalization_6[0][0]
__________________________________________________________________________________________________
conv2d_7 (Conv2D) (None, None, None, 1 73728 leaky_re_lu_6[0][0]
__________________________________________________________________________________________________
batch_normalization_7 (BatchNor (None, None, None, 1 512 conv2d_7[0][0]
__________________________________________________________________________________________________
leaky_re_lu_7 (LeakyReLU) (None, None, None, 1 0 batch_normalization_7[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, None, None, 1 0 leaky_re_lu_5[0][0]
leaky_re_lu_7[0][0]
__________________________________________________________________________________________________
conv2d_8 (Conv2D) (None, None, None, 6 8192 add_2[0][0]
__________________________________________________________________________________________________
batch_normalization_8 (BatchNor (None, None, None, 6 256 conv2d_8[0][0]
__________________________________________________________________________________________________
leaky_re_lu_8 (LeakyReLU) (None, None, None, 6 0 batch_normalization_8[0][0]
__________________________________________________________________________________________________
conv2d_9 (Conv2D) (None, None, None, 1 73728 leaky_re_lu_8[0][0]
__________________________________________________________________________________________________
batch_normalization_9 (BatchNor (None, None, None, 1 512 conv2d_9[0][0]
__________________________________________________________________________________________________
leaky_re_lu_9 (LeakyReLU) (None, None, None, 1 0 batch_normalization_9[0][0]
__________________________________________________________________________________________________
add_3 (Add) (None, None, None, 1 0 add_2[0][0]
leaky_re_lu_9[0][0]
__________________________________________________________________________________________________
zero_padding2d_3 (ZeroPadding2D (None, None, None, 1 0 add_3[0][0]
__________________________________________________________________________________________________
conv2d_10 (Conv2D) (None, None, None, 2 294912 zero_padding2d_3[0][0]
__________________________________________________________________________________________________
batch_normalization_10 (BatchNo (None, None, None, 2 1024 conv2d_10[0][0]
__________________________________________________________________________________________________
leaky_re_lu_10 (LeakyReLU) (None, None, None, 2 0 batch_normalization_10[0][0]
__________________________________________________________________________________________________
conv2d_11 (Conv2D) (None, None, None, 1 32768 leaky_re_lu_10[0][0]
__________________________________________________________________________________________________
batch_normalization_11 (BatchNo (None, None, None, 1 512 conv2d_11[0][0]
__________________________________________________________________________________________________
leaky_re_lu_11 (LeakyReLU) (None, None, None, 1 0 batch_normalization_11[0][0]
__________________________________________________________________________________________________
conv2d_12 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_11[0][0]
__________________________________________________________________________________________________
batch_normalization_12 (BatchNo (None, None, None, 2 1024 conv2d_12[0][0]
__________________________________________________________________________________________________
leaky_re_lu_12 (LeakyReLU) (None, None, None, 2 0 batch_normalization_12[0][0]
__________________________________________________________________________________________________
add_4 (Add) (None, None, None, 2 0 leaky_re_lu_10[0][0]
leaky_re_lu_12[0][0]
__________________________________________________________________________________________________
conv2d_13 (Conv2D) (None, None, None, 1 32768 add_4[0][0]
__________________________________________________________________________________________________
batch_normalization_13 (BatchNo (None, None, None, 1 512 conv2d_13[0][0]
__________________________________________________________________________________________________
leaky_re_lu_13 (LeakyReLU) (None, None, None, 1 0 batch_normalization_13[0][0]
__________________________________________________________________________________________________
conv2d_14 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_13[0][0]
__________________________________________________________________________________________________
batch_normalization_14 (BatchNo (None, None, None, 2 1024 conv2d_14[0][0]
__________________________________________________________________________________________________
leaky_re_lu_14 (LeakyReLU) (None, None, None, 2 0 batch_normalization_14[0][0]
__________________________________________________________________________________________________
add_5 (Add) (None, None, None, 2 0 add_4[0][0]
leaky_re_lu_14[0][0]
__________________________________________________________________________________________________
conv2d_15 (Conv2D) (None, None, None, 1 32768 add_5[0][0]
__________________________________________________________________________________________________
batch_normalization_15 (BatchNo (None, None, None, 1 512 conv2d_15[0][0]
__________________________________________________________________________________________________
leaky_re_lu_15 (LeakyReLU) (None, None, None, 1 0 batch_normalization_15[0][0]
__________________________________________________________________________________________________
conv2d_16 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_15[0][0]
__________________________________________________________________________________________________
batch_normalization_16 (BatchNo (None, None, None, 2 1024 conv2d_16[0][0]
__________________________________________________________________________________________________
leaky_re_lu_16 (LeakyReLU) (None, None, None, 2 0 batch_normalization_16[0][0]
__________________________________________________________________________________________________
add_6 (Add) (None, None, None, 2 0 add_5[0][0]
leaky_re_lu_16[0][0]
__________________________________________________________________________________________________
conv2d_17 (Conv2D) (None, None, None, 1 32768 add_6[0][0]
__________________________________________________________________________________________________
batch_normalization_17 (BatchNo (None, None, None, 1 512 conv2d_17[0][0]
__________________________________________________________________________________________________
leaky_re_lu_17 (LeakyReLU) (None, None, None, 1 0 batch_normalization_17[0][0]
__________________________________________________________________________________________________
conv2d_18 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_17[0][0]
__________________________________________________________________________________________________
batch_normalization_18 (BatchNo (None, None, None, 2 1024 conv2d_18[0][0]
__________________________________________________________________________________________________
leaky_re_lu_18 (LeakyReLU) (None, None, None, 2 0 batch_normalization_18[0][0]
__________________________________________________________________________________________________
add_7 (Add) (None, None, None, 2 0 add_6[0][0]
leaky_re_lu_18[0][0]
__________________________________________________________________________________________________
conv2d_19 (Conv2D) (None, None, None, 1 32768 add_7[0][0]
__________________________________________________________________________________________________
batch_normalization_19 (BatchNo (None, None, None, 1 512 conv2d_19[0][0]
__________________________________________________________________________________________________
leaky_re_lu_19 (LeakyReLU) (None, None, None, 1 0 batch_normalization_19[0][0]
__________________________________________________________________________________________________
conv2d_20 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_19[0][0]
__________________________________________________________________________________________________
batch_normalization_20 (BatchNo (None, None, None, 2 1024 conv2d_20[0][0]
__________________________________________________________________________________________________
leaky_re_lu_20 (LeakyReLU) (None, None, None, 2 0 batch_normalization_20[0][0]
__________________________________________________________________________________________________
add_8 (Add) (None, None, None, 2 0 add_7[0][0]
leaky_re_lu_20[0][0]
__________________________________________________________________________________________________
conv2d_21 (Conv2D) (None, None, None, 1 32768 add_8[0][0]
__________________________________________________________________________________________________
batch_normalization_21 (BatchNo (None, None, None, 1 512 conv2d_21[0][0]
__________________________________________________________________________________________________
leaky_re_lu_21 (LeakyReLU) (None, None, None, 1 0 batch_normalization_21[0][0]
__________________________________________________________________________________________________
conv2d_22 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_21[0][0]
__________________________________________________________________________________________________
batch_normalization_22 (BatchNo (None, None, None, 2 1024 conv2d_22[0][0]
__________________________________________________________________________________________________
leaky_re_lu_22 (LeakyReLU) (None, None, None, 2 0 batch_normalization_22[0][0]
__________________________________________________________________________________________________
add_9 (Add) (None, None, None, 2 0 add_8[0][0]
leaky_re_lu_22[0][0]
__________________________________________________________________________________________________
conv2d_23 (Conv2D) (None, None, None, 1 32768 add_9[0][0]
__________________________________________________________________________________________________
batch_normalization_23 (BatchNo (None, None, None, 1 512 conv2d_23[0][0]
__________________________________________________________________________________________________
leaky_re_lu_23 (LeakyReLU) (None, None, None, 1 0 batch_normalization_23[0][0]
__________________________________________________________________________________________________
conv2d_24 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_23[0][0]
__________________________________________________________________________________________________
batch_normalization_24 (BatchNo (None, None, None, 2 1024 conv2d_24[0][0]
__________________________________________________________________________________________________
leaky_re_lu_24 (LeakyReLU) (None, None, None, 2 0 batch_normalization_24[0][0]
__________________________________________________________________________________________________
add_10 (Add) (None, None, None, 2 0 add_9[0][0]
leaky_re_lu_24[0][0]
__________________________________________________________________________________________________
conv2d_25 (Conv2D) (None, None, None, 1 32768 add_10[0][0]
__________________________________________________________________________________________________
batch_normalization_25 (BatchNo (None, None, None, 1 512 conv2d_25[0][0]
__________________________________________________________________________________________________
leaky_re_lu_25 (LeakyReLU) (None, None, None, 1 0 batch_normalization_25[0][0]
__________________________________________________________________________________________________
conv2d_26 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_25[0][0]
__________________________________________________________________________________________________
batch_normalization_26 (BatchNo (None, None, None, 2 1024 conv2d_26[0][0]
__________________________________________________________________________________________________
leaky_re_lu_26 (LeakyReLU) (None, None, None, 2 0 batch_normalization_26[0][0]
__________________________________________________________________________________________________
add_11 (Add) (None, None, None, 2 0 add_10[0][0]
leaky_re_lu_26[0][0]
__________________________________________________________________________________________________
zero_padding2d_4 (ZeroPadding2D (None, None, None, 2 0 add_11[0][0]
__________________________________________________________________________________________________
conv2d_27 (Conv2D) (None, None, None, 5 1179648 zero_padding2d_4[0][0]
__________________________________________________________________________________________________
batch_normalization_27 (BatchNo (None, None, None, 5 2048 conv2d_27[0][0]
__________________________________________________________________________________________________
leaky_re_lu_27 (LeakyReLU) (None, None, None, 5 0 batch_normalization_27[0][0]
__________________________________________________________________________________________________
conv2d_28 (Conv2D) (None, None, None, 2 131072 leaky_re_lu_27[0][0]
__________________________________________________________________________________________________
batch_normalization_28 (BatchNo (None, None, None, 2 1024 conv2d_28[0][0]
__________________________________________________________________________________________________
leaky_re_lu_28 (LeakyReLU) (None, None, None, 2 0 batch_normalization_28[0][0]
__________________________________________________________________________________________________
conv2d_29 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_28[0][0]
__________________________________________________________________________________________________
batch_normalization_29 (BatchNo (None, None, None, 5 2048 conv2d_29[0][0]
__________________________________________________________________________________________________
leaky_re_lu_29 (LeakyReLU) (None, None, None, 5 0 batch_normalization_29[0][0]
__________________________________________________________________________________________________
add_12 (Add) (None, None, None, 5 0 leaky_re_lu_27[0][0]
leaky_re_lu_29[0][0]
__________________________________________________________________________________________________
conv2d_30 (Conv2D) (None, None, None, 2 131072 add_12[0][0]
__________________________________________________________________________________________________
batch_normalization_30 (BatchNo (None, None, None, 2 1024 conv2d_30[0][0]
__________________________________________________________________________________________________
leaky_re_lu_30 (LeakyReLU) (None, None, None, 2 0 batch_normalization_30[0][0]
__________________________________________________________________________________________________
conv2d_31 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_30[0][0]
__________________________________________________________________________________________________
batch_normalization_31 (BatchNo (None, None, None, 5 2048 conv2d_31[0][0]
__________________________________________________________________________________________________
leaky_re_lu_31 (LeakyReLU) (None, None, None, 5 0 batch_normalization_31[0][0]
__________________________________________________________________________________________________
add_13 (Add) (None, None, None, 5 0 add_12[0][0]
leaky_re_lu_31[0][0]
__________________________________________________________________________________________________
conv2d_32 (Conv2D) (None, None, None, 2 131072 add_13[0][0]
__________________________________________________________________________________________________
batch_normalization_32 (BatchNo (None, None, None, 2 1024 conv2d_32[0][0]
__________________________________________________________________________________________________
leaky_re_lu_32 (LeakyReLU) (None, None, None, 2 0 batch_normalization_32[0][0]
__________________________________________________________________________________________________
conv2d_33 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_32[0][0]
__________________________________________________________________________________________________
batch_normalization_33 (BatchNo (None, None, None, 5 2048 conv2d_33[0][0]
__________________________________________________________________________________________________
leaky_re_lu_33 (LeakyReLU) (None, None, None, 5 0 batch_normalization_33[0][0]
__________________________________________________________________________________________________
add_14 (Add) (None, None, None, 5 0 add_13[0][0]
leaky_re_lu_33[0][0]
__________________________________________________________________________________________________
conv2d_34 (Conv2D) (None, None, None, 2 131072 add_14[0][0]
__________________________________________________________________________________________________
batch_normalization_34 (BatchNo (None, None, None, 2 1024 conv2d_34[0][0]
__________________________________________________________________________________________________
leaky_re_lu_34 (LeakyReLU) (None, None, None, 2 0 batch_normalization_34[0][0]
__________________________________________________________________________________________________
conv2d_35 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_34[0][0]
__________________________________________________________________________________________________
batch_normalization_35 (BatchNo (None, None, None, 5 2048 conv2d_35[0][0]
__________________________________________________________________________________________________
leaky_re_lu_35 (LeakyReLU) (None, None, None, 5 0 batch_normalization_35[0][0]
__________________________________________________________________________________________________
add_15 (Add) (None, None, None, 5 0 add_14[0][0]
leaky_re_lu_35[0][0]
__________________________________________________________________________________________________
conv2d_36 (Conv2D) (None, None, None, 2 131072 add_15[0][0]
__________________________________________________________________________________________________
batch_normalization_36 (BatchNo (None, None, None, 2 1024 conv2d_36[0][0]
__________________________________________________________________________________________________
leaky_re_lu_36 (LeakyReLU) (None, None, None, 2 0 batch_normalization_36[0][0]
__________________________________________________________________________________________________
conv2d_37 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_36[0][0]
__________________________________________________________________________________________________
batch_normalization_37 (BatchNo (None, None, None, 5 2048 conv2d_37[0][0]
__________________________________________________________________________________________________
leaky_re_lu_37 (LeakyReLU) (None, None, None, 5 0 batch_normalization_37[0][0]
__________________________________________________________________________________________________
add_16 (Add) (None, None, None, 5 0 add_15[0][0]
leaky_re_lu_37[0][0]
__________________________________________________________________________________________________
conv2d_38 (Conv2D) (None, None, None, 2 131072 add_16[0][0]
__________________________________________________________________________________________________
batch_normalization_38 (BatchNo (None, None, None, 2 1024 conv2d_38[0][0]
__________________________________________________________________________________________________
leaky_re_lu_38 (LeakyReLU) (None, None, None, 2 0 batch_normalization_38[0][0]
__________________________________________________________________________________________________
conv2d_39 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_38[0][0]
__________________________________________________________________________________________________
batch_normalization_39 (BatchNo (None, None, None, 5 2048 conv2d_39[0][0]
__________________________________________________________________________________________________
leaky_re_lu_39 (LeakyReLU) (None, None, None, 5 0 batch_normalization_39[0][0]
__________________________________________________________________________________________________
add_17 (Add) (None, None, None, 5 0 add_16[0][0]
leaky_re_lu_39[0][0]
__________________________________________________________________________________________________
conv2d_40 (Conv2D) (None, None, None, 2 131072 add_17[0][0]
__________________________________________________________________________________________________
batch_normalization_40 (BatchNo (None, None, None, 2 1024 conv2d_40[0][0]
__________________________________________________________________________________________________
leaky_re_lu_40 (LeakyReLU) (None, None, None, 2 0 batch_normalization_40[0][0]
__________________________________________________________________________________________________
conv2d_41 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_40[0][0]
__________________________________________________________________________________________________
batch_normalization_41 (BatchNo (None, None, None, 5 2048 conv2d_41[0][0]
__________________________________________________________________________________________________
leaky_re_lu_41 (LeakyReLU) (None, None, None, 5 0 batch_normalization_41[0][0]
__________________________________________________________________________________________________
add_18 (Add) (None, None, None, 5 0 add_17[0][0]
leaky_re_lu_41[0][0]
__________________________________________________________________________________________________
conv2d_42 (Conv2D) (None, None, None, 2 131072 add_18[0][0]
__________________________________________________________________________________________________
batch_normalization_42 (BatchNo (None, None, None, 2 1024 conv2d_42[0][0]
__________________________________________________________________________________________________
leaky_re_lu_42 (LeakyReLU) (None, None, None, 2 0 batch_normalization_42[0][0]
__________________________________________________________________________________________________
conv2d_43 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_42[0][0]
__________________________________________________________________________________________________
batch_normalization_43 (BatchNo (None, None, None, 5 2048 conv2d_43[0][0]
__________________________________________________________________________________________________
leaky_re_lu_43 (LeakyReLU) (None, None, None, 5 0 batch_normalization_43[0][0]
__________________________________________________________________________________________________
add_19 (Add) (None, None, None, 5 0 add_18[0][0]
leaky_re_lu_43[0][0]
__________________________________________________________________________________________________
zero_padding2d_5 (ZeroPadding2D (None, None, None, 5 0 add_19[0][0]
__________________________________________________________________________________________________
conv2d_44 (Conv2D) (None, None, None, 1 4718592 zero_padding2d_5[0][0]
__________________________________________________________________________________________________
batch_normalization_44 (BatchNo (None, None, None, 1 4096 conv2d_44[0][0]
__________________________________________________________________________________________________
leaky_re_lu_44 (LeakyReLU) (None, None, None, 1 0 batch_normalization_44[0][0]
__________________________________________________________________________________________________
conv2d_45 (Conv2D) (None, None, None, 5 524288 leaky_re_lu_44[0][0]
__________________________________________________________________________________________________
batch_normalization_45 (BatchNo (None, None, None, 5 2048 conv2d_45[0][0]
__________________________________________________________________________________________________
leaky_re_lu_45 (LeakyReLU) (None, None, None, 5 0 batch_normalization_45[0][0]
__________________________________________________________________________________________________
conv2d_46 (Conv2D) (None, None, None, 1 4718592 leaky_re_lu_45[0][0]
__________________________________________________________________________________________________
batch_normalization_46 (BatchNo (None, None, None, 1 4096 conv2d_46[0][0]
__________________________________________________________________________________________________
leaky_re_lu_46 (LeakyReLU) (None, None, None, 1 0 batch_normalization_46[0][0]
__________________________________________________________________________________________________
add_20 (Add) (None, None, None, 1 0 leaky_re_lu_44[0][0]
leaky_re_lu_46[0][0]
__________________________________________________________________________________________________
conv2d_47 (Conv2D) (None, None, None, 5 524288 add_20[0][0]
__________________________________________________________________________________________________
batch_normalization_47 (BatchNo (None, None, None, 5 2048 conv2d_47[0][0]
__________________________________________________________________________________________________
leaky_re_lu_47 (LeakyReLU) (None, None, None, 5 0 batch_normalization_47[0][0]
__________________________________________________________________________________________________
conv2d_48 (Conv2D) (None, None, None, 1 4718592 leaky_re_lu_47[0][0]
__________________________________________________________________________________________________
batch_normalization_48 (BatchNo (None, None, None, 1 4096 conv2d_48[0][0]
__________________________________________________________________________________________________
leaky_re_lu_48 (LeakyReLU) (None, None, None, 1 0 batch_normalization_48[0][0]
__________________________________________________________________________________________________
add_21 (Add) (None, None, None, 1 0 add_20[0][0]
leaky_re_lu_48[0][0]
__________________________________________________________________________________________________
conv2d_49 (Conv2D) (None, None, None, 5 524288 add_21[0][0]
__________________________________________________________________________________________________
batch_normalization_49 (BatchNo (None, None, None, 5 2048 conv2d_49[0][0]
__________________________________________________________________________________________________
leaky_re_lu_49 (LeakyReLU) (None, None, None, 5 0 batch_normalization_49[0][0]
__________________________________________________________________________________________________
conv2d_50 (Conv2D) (None, None, None, 1 4718592 leaky_re_lu_49[0][0]
__________________________________________________________________________________________________
batch_normalization_50 (BatchNo (None, None, None, 1 4096 conv2d_50[0][0]
__________________________________________________________________________________________________
leaky_re_lu_50 (LeakyReLU) (None, None, None, 1 0 batch_normalization_50[0][0]
__________________________________________________________________________________________________
add_22 (Add) (None, None, None, 1 0 add_21[0][0]
leaky_re_lu_50[0][0]
__________________________________________________________________________________________________
conv2d_51 (Conv2D) (None, None, None, 5 524288 add_22[0][0]
__________________________________________________________________________________________________
batch_normalization_51 (BatchNo (None, None, None, 5 2048 conv2d_51[0][0]
__________________________________________________________________________________________________
leaky_re_lu_51 (LeakyReLU) (None, None, None, 5 0 batch_normalization_51[0][0]
__________________________________________________________________________________________________
conv2d_52 (Conv2D) (None, None, None, 1 4718592 leaky_re_lu_51[0][0]
__________________________________________________________________________________________________
batch_normalization_52 (BatchNo (None, None, None, 1 4096 conv2d_52[0][0]
__________________________________________________________________________________________________
leaky_re_lu_52 (LeakyReLU) (None, None, None, 1 0 batch_normalization_52[0][0]
__________________________________________________________________________________________________
add_23 (Add) (None, None, None, 1 0 add_22[0][0]
leaky_re_lu_52[0][0]
__________________________________________________________________________________________________
conv2d_53 (Conv2D) (None, None, None, 5 524288 add_23[0][0]
__________________________________________________________________________________________________
batch_normalization_53 (BatchNo (None, None, None, 5 2048 conv2d_53[0][0]
__________________________________________________________________________________________________
leaky_re_lu_53 (LeakyReLU) (None, None, None, 5 0 batch_normalization_53[0][0]
__________________________________________________________________________________________________
conv2d_54 (Conv2D) (None, None, None, 1 4718592 leaky_re_lu_53[0][0]
__________________________________________________________________________________________________
batch_normalization_54 (BatchNo (None, None, None, 1 4096 conv2d_54[0][0]
__________________________________________________________________________________________________
leaky_re_lu_54 (LeakyReLU) (None, None, None, 1 0 batch_normalization_54[0][0]
__________________________________________________________________________________________________
conv2d_55 (Conv2D) (None, None, None, 5 524288 leaky_re_lu_54[0][0]
__________________________________________________________________________________________________
batch_normalization_55 (BatchNo (None, None, None, 5 2048 conv2d_55[0][0]
__________________________________________________________________________________________________
leaky_re_lu_55 (LeakyReLU) (None, None, None, 5 0 batch_normalization_55[0][0]
__________________________________________________________________________________________________
conv2d_56 (Conv2D) (None, None, None, 1 4718592 leaky_re_lu_55[0][0]
__________________________________________________________________________________________________
batch_normalization_56 (BatchNo (None, None, None, 1 4096 conv2d_56[0][0]
__________________________________________________________________________________________________
leaky_re_lu_56 (LeakyReLU) (None, None, None, 1 0 batch_normalization_56[0][0]
__________________________________________________________________________________________________
conv2d_57 (Conv2D) (None, None, None, 5 524288 leaky_re_lu_56[0][0]
__________________________________________________________________________________________________
batch_normalization_57 (BatchNo (None, None, None, 5 2048 conv2d_57[0][0]
__________________________________________________________________________________________________
leaky_re_lu_57 (LeakyReLU) (None, None, None, 5 0 batch_normalization_57[0][0]
__________________________________________________________________________________________________
conv2d_60 (Conv2D) (None, None, None, 2 131072 leaky_re_lu_57[0][0]
__________________________________________________________________________________________________
batch_normalization_59 (BatchNo (None, None, None, 2 1024 conv2d_60[0][0]
__________________________________________________________________________________________________
leaky_re_lu_59 (LeakyReLU) (None, None, None, 2 0 batch_normalization_59[0][0]
__________________________________________________________________________________________________
up_sampling2d_1 (UpSampling2D) (None, None, None, 2 0 leaky_re_lu_59[0][0]
__________________________________________________________________________________________________
concatenate_1 (Concatenate) (None, None, None, 7 0 up_sampling2d_1[0][0]
add_19[0][0]
__________________________________________________________________________________________________
conv2d_61 (Conv2D) (None, None, None, 2 196608 concatenate_1[0][0]
__________________________________________________________________________________________________
batch_normalization_60 (BatchNo (None, None, None, 2 1024 conv2d_61[0][0]
__________________________________________________________________________________________________
leaky_re_lu_60 (LeakyReLU) (None, None, None, 2 0 batch_normalization_60[0][0]
__________________________________________________________________________________________________
conv2d_62 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_60[0][0]
__________________________________________________________________________________________________
batch_normalization_61 (BatchNo (None, None, None, 5 2048 conv2d_62[0][0]
__________________________________________________________________________________________________
leaky_re_lu_61 (LeakyReLU) (None, None, None, 5 0 batch_normalization_61[0][0]
__________________________________________________________________________________________________
conv2d_63 (Conv2D) (None, None, None, 2 131072 leaky_re_lu_61[0][0]
__________________________________________________________________________________________________
batch_normalization_62 (BatchNo (None, None, None, 2 1024 conv2d_63[0][0]
__________________________________________________________________________________________________
leaky_re_lu_62 (LeakyReLU) (None, None, None, 2 0 batch_normalization_62[0][0]
__________________________________________________________________________________________________
conv2d_64 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_62[0][0]
__________________________________________________________________________________________________
batch_normalization_63 (BatchNo (None, None, None, 5 2048 conv2d_64[0][0]
__________________________________________________________________________________________________
leaky_re_lu_63 (LeakyReLU) (None, None, None, 5 0 batch_normalization_63[0][0]
__________________________________________________________________________________________________
conv2d_65 (Conv2D) (None, None, None, 2 131072 leaky_re_lu_63[0][0]
__________________________________________________________________________________________________
batch_normalization_64 (BatchNo (None, None, None, 2 1024 conv2d_65[0][0]
__________________________________________________________________________________________________
leaky_re_lu_64 (LeakyReLU) (None, None, None, 2 0 batch_normalization_64[0][0]
__________________________________________________________________________________________________
conv2d_68 (Conv2D) (None, None, None, 1 32768 leaky_re_lu_64[0][0]
__________________________________________________________________________________________________
batch_normalization_66 (BatchNo (None, None, None, 1 512 conv2d_68[0][0]
__________________________________________________________________________________________________
leaky_re_lu_66 (LeakyReLU) (None, None, None, 1 0 batch_normalization_66[0][0]
__________________________________________________________________________________________________
up_sampling2d_2 (UpSampling2D) (None, None, None, 1 0 leaky_re_lu_66[0][0]
__________________________________________________________________________________________________
concatenate_2 (Concatenate) (None, None, None, 3 0 up_sampling2d_2[0][0]
add_11[0][0]
__________________________________________________________________________________________________
conv2d_69 (Conv2D) (None, None, None, 1 49152 concatenate_2[0][0]
__________________________________________________________________________________________________
batch_normalization_67 (BatchNo (None, None, None, 1 512 conv2d_69[0][0]
__________________________________________________________________________________________________
leaky_re_lu_67 (LeakyReLU) (None, None, None, 1 0 batch_normalization_67[0][0]
__________________________________________________________________________________________________
conv2d_70 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_67[0][0]
__________________________________________________________________________________________________
batch_normalization_68 (BatchNo (None, None, None, 2 1024 conv2d_70[0][0]
__________________________________________________________________________________________________
leaky_re_lu_68 (LeakyReLU) (None, None, None, 2 0 batch_normalization_68[0][0]
__________________________________________________________________________________________________
conv2d_71 (Conv2D) (None, None, None, 1 32768 leaky_re_lu_68[0][0]
__________________________________________________________________________________________________
batch_normalization_69 (BatchNo (None, None, None, 1 512 conv2d_71[0][0]
__________________________________________________________________________________________________
leaky_re_lu_69 (LeakyReLU) (None, None, None, 1 0 batch_normalization_69[0][0]
__________________________________________________________________________________________________
conv2d_72 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_69[0][0]
__________________________________________________________________________________________________
batch_normalization_70 (BatchNo (None, None, None, 2 1024 conv2d_72[0][0]
__________________________________________________________________________________________________
leaky_re_lu_70 (LeakyReLU) (None, None, None, 2 0 batch_normalization_70[0][0]
__________________________________________________________________________________________________
conv2d_73 (Conv2D) (None, None, None, 1 32768 leaky_re_lu_70[0][0]
__________________________________________________________________________________________________
batch_normalization_71 (BatchNo (None, None, None, 1 512 conv2d_73[0][0]
__________________________________________________________________________________________________
leaky_re_lu_71 (LeakyReLU) (None, None, None, 1 0 batch_normalization_71[0][0]
__________________________________________________________________________________________________
conv2d_58 (Conv2D) (None, None, None, 1 4718592 leaky_re_lu_57[0][0]
__________________________________________________________________________________________________
conv2d_66 (Conv2D) (None, None, None, 5 1179648 leaky_re_lu_64[0][0]
__________________________________________________________________________________________________
conv2d_74 (Conv2D) (None, None, None, 2 294912 leaky_re_lu_71[0][0]
__________________________________________________________________________________________________
batch_normalization_58 (BatchNo (None, None, None, 1 4096 conv2d_58[0][0]
__________________________________________________________________________________________________
batch_normalization_65 (BatchNo (None, None, None, 5 2048 conv2d_66[0][0]
__________________________________________________________________________________________________
batch_normalization_72 (BatchNo (None, None, None, 2 1024 conv2d_74[0][0]
__________________________________________________________________________________________________
leaky_re_lu_58 (LeakyReLU) (None, None, None, 1 0 batch_normalization_58[0][0]
__________________________________________________________________________________________________
leaky_re_lu_65 (LeakyReLU) (None, None, None, 5 0 batch_normalization_65[0][0]
__________________________________________________________________________________________________
leaky_re_lu_72 (LeakyReLU) (None, None, None, 2 0 batch_normalization_72[0][0]
__________________________________________________________________________________________________
conv2d_59 (Conv2D) (None, None, None, 2 261375 leaky_re_lu_58[0][0]
__________________________________________________________________________________________________
conv2d_67 (Conv2D) (None, None, None, 2 130815 leaky_re_lu_65[0][0]
__________________________________________________________________________________________________
conv2d_75 (Conv2D) (None, None, None, 2 65535 leaky_re_lu_72[0][0]
==================================================================================================
Total params: 62,001,757
Trainable params: 61,949,149
Non-trainable params: 52,608
__________________________________________________________________________________________________
None
Saved Keras model to model_data/yolo.h5
Read 62001757 of 62001757.0 from Darknet weights.
- convert it to coreml model. h5_coreml_full.py is the very same thing as your script https://github.com/Ma-Dan/YOLOv3-CoreML/blob/master/Convert/coreml.py, only with the input file moved to command argument.
$ python h5_coreml_full.py model_data/yolo.h5
WARNING:root:Keras version 2.1.5 detected. Last version known to be fully compatible of Keras is 2.1.3 .
WARNING:root:TensorFlow version 1.6.0 detected. Last version known to be fully compatible is 1.5.0 .
2018-06-18 10:04:56.709285: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
/home/xuzh/convert_yolo_to_coreml/coremltools/lib/python3.6/site-packages/keras/models.py:255: UserWarning: No training configuration found in save file: the model was *not* compiled. Compile it manually.
warnings.warn('No training configuration found in save file: '
0 : input_1, <keras.engine.topology.InputLayer object at 0x7f98b1961b70>
1 : conv2d_1, <keras.layers.convolutional.Conv2D object at 0x7f98b1961be0>
2 : batch_normalization_1, <keras.layers.normalization.BatchNormalization object at 0x7f98b1961ef0>
3 : leaky_re_lu_1, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b1961eb8>
4 : zero_padding2d_1, <keras.layers.convolutional.ZeroPadding2D object at 0x7f98b18f9278>
5 : conv2d_2, <keras.layers.convolutional.Conv2D object at 0x7f98b18f92e8>
6 : batch_normalization_2, <keras.layers.normalization.BatchNormalization object at 0x7f98b18f9470>
7 : leaky_re_lu_2, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b18f95c0>
8 : conv2d_3, <keras.layers.convolutional.Conv2D object at 0x7f98b18f95f8>
9 : batch_normalization_3, <keras.layers.normalization.BatchNormalization object at 0x7f98b18f9780>
10 : leaky_re_lu_3, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b18f98d0>
11 : conv2d_4, <keras.layers.convolutional.Conv2D object at 0x7f98b18f9908>
12 : batch_normalization_4, <keras.layers.normalization.BatchNormalization object at 0x7f98b18f9a90>
13 : leaky_re_lu_4, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b18f9be0>
14 : add_1, <keras.layers.merge.Add object at 0x7f98b18f9c18>
15 : zero_padding2d_2, <keras.layers.convolutional.ZeroPadding2D object at 0x7f98b18f9c50>
16 : conv2d_5, <keras.layers.convolutional.Conv2D object at 0x7f98b18f9cc0>
17 : batch_normalization_5, <keras.layers.normalization.BatchNormalization object at 0x7f98b18f9e48>
18 : leaky_re_lu_5, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b18f9f98>
19 : conv2d_6, <keras.layers.convolutional.Conv2D object at 0x7f98b1961fd0>
20 : batch_normalization_6, <keras.layers.normalization.BatchNormalization object at 0x7f98b18ff198>
21 : leaky_re_lu_6, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b18ff2e8>
22 : conv2d_7, <keras.layers.convolutional.Conv2D object at 0x7f98b18ff320>
23 : batch_normalization_7, <keras.layers.normalization.BatchNormalization object at 0x7f98b18ff4a8>
24 : leaky_re_lu_7, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b18ff5f8>
25 : add_2, <keras.layers.merge.Add object at 0x7f98b18ff630>
26 : conv2d_8, <keras.layers.convolutional.Conv2D object at 0x7f98b18ff668>
27 : batch_normalization_8, <keras.layers.normalization.BatchNormalization object at 0x7f98b18ff7f0>
28 : leaky_re_lu_8, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b18ff940>
29 : conv2d_9, <keras.layers.convolutional.Conv2D object at 0x7f98b18ff978>
30 : batch_normalization_9, <keras.layers.normalization.BatchNormalization object at 0x7f98b18ffb00>
31 : leaky_re_lu_9, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b18ffc50>
32 : add_3, <keras.layers.merge.Add object at 0x7f98b18ffc88>
33 : zero_padding2d_3, <keras.layers.convolutional.ZeroPadding2D object at 0x7f98b18ffcc0>
34 : conv2d_10, <keras.layers.convolutional.Conv2D object at 0x7f98b18ffd30>
35 : batch_normalization_10, <keras.layers.normalization.BatchNormalization object at 0x7f98b18ffeb8>
36 : leaky_re_lu_10, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b18f9fd0>
37 : conv2d_11, <keras.layers.convolutional.Conv2D object at 0x7f98b190d080>
38 : batch_normalization_11, <keras.layers.normalization.BatchNormalization object at 0x7f98b190d208>
39 : leaky_re_lu_11, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b190d358>
40 : conv2d_12, <keras.layers.convolutional.Conv2D object at 0x7f98b190d390>
41 : batch_normalization_12, <keras.layers.normalization.BatchNormalization object at 0x7f98b190d518>
42 : leaky_re_lu_12, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b190d668>
43 : add_4, <keras.layers.merge.Add object at 0x7f98b190d6a0>
44 : conv2d_13, <keras.layers.convolutional.Conv2D object at 0x7f98b190d6d8>
45 : batch_normalization_13, <keras.layers.normalization.BatchNormalization object at 0x7f98b190d860>
46 : leaky_re_lu_13, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b190d9b0>
47 : conv2d_14, <keras.layers.convolutional.Conv2D object at 0x7f98b190d9e8>
48 : batch_normalization_14, <keras.layers.normalization.BatchNormalization object at 0x7f98b190db70>
49 : leaky_re_lu_14, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b190dcc0>
50 : add_5, <keras.layers.merge.Add object at 0x7f98b190dcf8>
51 : conv2d_15, <keras.layers.convolutional.Conv2D object at 0x7f98b190dd30>
52 : batch_normalization_15, <keras.layers.normalization.BatchNormalization object at 0x7f98b190deb8>
53 : leaky_re_lu_15, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b18fffd0>
54 : conv2d_16, <keras.layers.convolutional.Conv2D object at 0x7f98b1915080>
55 : batch_normalization_16, <keras.layers.normalization.BatchNormalization object at 0x7f98b1915208>
56 : leaky_re_lu_16, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b1915358>
57 : add_6, <keras.layers.merge.Add object at 0x7f98b1915390>
58 : conv2d_17, <keras.layers.convolutional.Conv2D object at 0x7f98b19153c8>
59 : batch_normalization_17, <keras.layers.normalization.BatchNormalization object at 0x7f98b1915550>
60 : leaky_re_lu_17, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b19156a0>
61 : conv2d_18, <keras.layers.convolutional.Conv2D object at 0x7f98b19156d8>
62 : batch_normalization_18, <keras.layers.normalization.BatchNormalization object at 0x7f98b1915860>
63 : leaky_re_lu_18, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b19159b0>
64 : add_7, <keras.layers.merge.Add object at 0x7f98b19159e8>
65 : conv2d_19, <keras.layers.convolutional.Conv2D object at 0x7f98b1915a20>
66 : batch_normalization_19, <keras.layers.normalization.BatchNormalization object at 0x7f98b1915ba8>
67 : leaky_re_lu_19, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b1915cf8>
68 : conv2d_20, <keras.layers.convolutional.Conv2D object at 0x7f98b1915d30>
69 : batch_normalization_20, <keras.layers.normalization.BatchNormalization object at 0x7f98b1915eb8>
70 : leaky_re_lu_20, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b190dfd0>
71 : add_8, <keras.layers.merge.Add object at 0x7f98b191c080>
72 : conv2d_21, <keras.layers.convolutional.Conv2D object at 0x7f98b191c0b8>
73 : batch_normalization_21, <keras.layers.normalization.BatchNormalization object at 0x7f98b191c240>
74 : leaky_re_lu_21, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b191c390>
75 : conv2d_22, <keras.layers.convolutional.Conv2D object at 0x7f98b191c3c8>
76 : batch_normalization_22, <keras.layers.normalization.BatchNormalization object at 0x7f98b191c550>
77 : leaky_re_lu_22, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b191c6a0>
78 : add_9, <keras.layers.merge.Add object at 0x7f98b191c6d8>
79 : conv2d_23, <keras.layers.convolutional.Conv2D object at 0x7f98b191c710>
80 : batch_normalization_23, <keras.layers.normalization.BatchNormalization object at 0x7f98b191c898>
81 : leaky_re_lu_23, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b191c9e8>
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83 : batch_normalization_24, <keras.layers.normalization.BatchNormalization object at 0x7f98b191cba8>
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237 : conv2d_73, <keras.layers.convolutional.Conv2D object at 0x7f98b1864b70>
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240 : conv2d_58, <keras.layers.convolutional.Conv2D object at 0x7f98b1864e80>
241 : conv2d_66, <keras.layers.convolutional.Conv2D object at 0x7f98b18dcf98>
242 : conv2d_74, <keras.layers.convolutional.Conv2D object at 0x7f98b186a208>
243 : batch_normalization_58, <keras.layers.normalization.BatchNormalization object at 0x7f98b186a3c8>
244 : batch_normalization_65, <keras.layers.normalization.BatchNormalization object at 0x7f98b186a518>
245 : batch_normalization_72, <keras.layers.normalization.BatchNormalization object at 0x7f98b186a630>
246 : leaky_re_lu_58, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b186a748>
247 : leaky_re_lu_65, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b186a780>
248 : leaky_re_lu_72, <keras.layers.advanced_activations.LeakyReLU object at 0x7f98b186a7b8>
249 : conv2d_59, <keras.layers.convolutional.Conv2D object at 0x7f98b186a7f0>
250 : conv2d_67, <keras.layers.convolutional.Conv2D object at 0x7f98b186a978>
251 : conv2d_75, <keras.layers.convolutional.Conv2D object at 0x7f98b186ab38>
Traceback (most recent call last):
File "h5_coreml_full.py", line 5, in <module>
image_input_names='input1', output_names=['output1', 'output2', 'output3'], image_scale=1/255.)
File "/home/xuzh/convert_yolo_to_coreml/coremltools/lib/python3.6/site-packages/coremltools/converters/keras/_keras_converter.py", line 745, in convert
custom_conversion_functions=custom_conversion_functions)
File "/home/xuzh/convert_yolo_to_coreml/coremltools/lib/python3.6/site-packages/coremltools/converters/keras/_keras_converter.py", line 543, in convertToSpec
custom_objects=custom_objects)
File "/home/xuzh/convert_yolo_to_coreml/coremltools/lib/python3.6/site-packages/coremltools/converters/keras/_keras2_converter.py", line 350, in _convert
image_scale = image_scale)
File "/home/xuzh/convert_yolo_to_coreml/coremltools/lib/python3.6/site-packages/coremltools/models/neural_network.py", line 2542, in set_pre_processing_parameters
channels, height, width = array_shape
ValueError: not enough values to unpack (expected 3, got 1)
Please help and let me know how to get this resolved.
my environment(which is tested/required in keras-yolo3):
virtualenv -p /usr/bin/python36 coremltools
source coremltools/bin/activate
pip install keras==2.1.5
tensorflow==1.6.0
pip install -U coremltools
pip install h5py
This might be of use. I had the unpack issue and was able to solve it by specifying a defined input shape
https://github.com/apple/coremltools/issues/203
Same thing happened to me. It was because the convert.py script didn't specify the dimensions.
So simply change line 88 of file (https://github.com/qqwweee/keras-yolo3/blob/master/convert.py#L88) from
input_layer = Input(shape=(None, None, 3))
to
input_layer = Input(shape=(416, 416, 3))
Hope this helps!
