ValueError: cannot reshape array of size 2048 into shape (18,1024,1,1)

[dsbyprateekg]

Hi,

I am trying to convert my custom YOLOv4 weights to TF using below command- python save_model.py --weights ./data/yolo-obj_best.weights --output ./checkpoints/yolov4-704 --input_size 704 --model yolov4

But getting below error- File "save_model.py", line 58, in <module> app.run(main) File "/usr/local/lib/python3.6/dist-packages/absl/app.py", line 299, in run _run_main(main, args) File "/usr/local/lib/python3.6/dist-packages/absl/app.py", line 250, in _run_main sys.exit(main(argv)) File "save_model.py", line 54, in main save_tf() File "save_model.py", line 49, in save_tf utils.load_weights(model, FLAGS.weights, FLAGS.model, FLAGS.tiny) File "/content/drive/My Drive/kaggle/tensorflow-yolov4-tflite/core/utils.py", line 63, in load_weights conv_weights = conv_weights.reshape(conv_shape).transpose([2, 3, 1, 0]) ValueError: cannot reshape array of size 2048 into shape (18,1024,1,1)

I have only one class in my data/classes/obj.names file- obj.txt

Please suggest how to solve this error.

[vladimirhorvat]

Me as well, but with yolov4-tiny!

[dsbyprateekg]

@vladimirhorvat I am able to successfully do the conversion but using below repository- https://github.com/david8862/keras-YOLOv3-model-set

[vladimirhorvat]

Thank you. It's a good lead, although it doesn't work for tiny.

[tobymcclean]

Any resolutions to this. My change from the default instructions at https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects is to also include the changes recommended in "for training for small objects" which is part of https://github.com/AlexeyAB/darknet#how-to-improve-object-detection

[dsbyprateekg]

@tobymcclean I recommend you to use following repo- https://github.com/david8862/keras-YOLOv3-model-set

The author of above repo is more active and replies asap. With this repo, I am able to convert my custom YOLOv4 into keras model.

[AlexanderSoroka]

I've just got exactly the same issue trying to convert tiny weights file trained with custom dataset following the instructions at https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects and to convert weights to checkpoint I defined class list in the file data/classes/custom.names (one class per line) and pointed the code to use this classes here: https://github.com/hunglc007/tensorflow-yolov4-tflite/blob/master/core/config.py#L14 After this change convert succeeded

[cpshaheen]

I've just got exactly the same issue trying to convert tiny weights file trained with custom dataset following the instructions at https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects and to convert weights to checkpoint I defined class list in the file data/classes/custom.names (one class per line) and pointed the code to use this classes here: https://github.com/hunglc007/tensorflow-yolov4-tflite/blob/master/core/config.py#L14 After this change convert succeeded

I can confirm this is the solution - @hunglc007 please add command line argument support inorder to provide classnames to avoid future issues

[Farjad3253]

Getting the same issue but not still resolved by me. Any suggestions?

[victoriest]

Getting the same issue but not still resolved by me. Any suggestions?

me to #193

[hamhochoi]

I've just got exactly the same issue trying to convert tiny weights file trained with custom dataset following the instructions at https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects and to convert weights to checkpoint I defined class list in the file data/classes/custom.names (one class per line) and pointed the code to use this classes here: https://github.com/hunglc007/tensorflow-yolov4-tflite/blob/master/core/config.py#L14 After this change convert succeeded

Thanks, this work for me!

[albertoisorna]

I've just got exactly the same issue trying to convert tiny weights file trained with custom dataset following the instructions at https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects and to convert weights to checkpoint I defined class list in the file data/classes/custom.names (one class per line) and pointed the code to use this classes here: https://github.com/hunglc007/tensorflow-yolov4-tflite/blob/master/core/config.py#L14 After this change convert succeeded

Please could you detail a bit more this? Is just to change the default coco.names with your own one?

[hamhochoi]

Maybe it because of the absolute path makes things work.

[quickgrid]

I've just got exactly the same issue trying to convert tiny weights file trained with custom dataset following the instructions at https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects and to convert weights to checkpoint I defined class list in the file data/classes/custom.names (one class per line) and pointed the code to use this classes here: https://github.com/hunglc007/tensorflow-yolov4-tflite/blob/master/core/config.py#L14 After this change convert succeeded

Thank you. Conversion and inference worked for me after correcting this.

[zoltanszalontay]

I can confirm this is the solution - @hunglc007 please add command line argument support inorder to provide classnames to avoid future issues

Supposing you're using Colab this command modifies the file name !sed -i "s/coco.names/custom.names/g" /content/tensorflow-yolov4-tflite/core/config.py

[wsora]

Getting the same issue but not still resolved by me. Any suggestions?

When train darknet,did you edit your custom *.cfg based on yolov4-custom.cfg instead of yolov4.cfg? There are some different in these two cfg data. You can edit your custom cfg based on yolov4.cfg and train again,that is how I solve the issue.

[Ehabur]

try to check class names defines properly

[JeremyDemers]

More updated code hosted by theAIGuysCode https://github.com/theAIGuysCode/tensorflow-yolov4-tflite. Has the instructions with images on what to change for the names when custom training.

[joeng03]

I still don't understand how to solve this problem, can anyone explain it to me? Thanks

[ssimon0327tw]

I had the same question like this，I tried all the suggestion above this coment，but still not got solved.... Had checked config.py "__C.YOLO.CLASSES = "./data/classes/*.names"" and *.names is just one class per line.(My calss id only one class lol) I also train my weights again followed Alexey's git . but it don't work...... anyone can help me ? Thanks.

[bhaecker]

I used black and white images to train, which means that I had to change the channel number to 1 in input_layer, line 19 in save_model.py:

input_layer = tf.keras.layers.Input([FLAGS.input_size, FLAGS.input_size, 1])

[shafaattahir]

Simple solution Add the bellow code into /content/yolov4-deepsort/core/config.py ''' from easydict import EasyDict as edict

__C = edict()

Consumers can get config by: from config import cfg

cfg = __C

YOLO options

__C.YOLO = edict()

__C.YOLO.CLASSES = "./data/classes/coco.names" __C.YOLO.ANCHORS = [12,16, 19,36, 40,28, 36,75, 76,55, 72,146, 142,110, 192,243, 459,401] __C.YOLO.ANCHORS_V3 = [10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326] __C.YOLO.ANCHORS_TINY = [23,27, 37,58, 81,82, 81,82, 135,169, 344,319] __C.YOLO.STRIDES = [8, 16, 32] __C.YOLO.STRIDES_TINY = [16, 32] __C.YOLO.XYSCALE = [1.2, 1.1, 1.05] __C.YOLO.XYSCALE_TINY = [1.05, 1.05] __C.YOLO.ANCHOR_PER_SCALE = 3 __C.YOLO.IOU_LOSS_THRESH = 0.5

Train options

__C.TRAIN = edict()

__C.TRAIN.ANNOT_PATH = "./data/dataset/val2017.txt" __C.TRAIN.BATCH_SIZE = 2

__C.TRAIN.INPUT_SIZE = [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]

__C.TRAIN.INPUT_SIZE = 416 __C.TRAIN.DATA_AUG = True __C.TRAIN.LR_INIT = 1e-3 __C.TRAIN.LR_END = 1e-6 __C.TRAIN.WARMUP_EPOCHS = 2 __C.TRAIN.FISRT_STAGE_EPOCHS = 20 __C.TRAIN.SECOND_STAGE_EPOCHS = 30

TEST options

__C.TEST = edict()

__C.TEST.ANNOT_PATH = "./data/dataset/val2017.txt" __C.TEST.BATCH_SIZE = 2 __C.TEST.INPUT_SIZE = 416 __C.TEST.DATA_AUG = False __C.TEST.DECTECTED_IMAGE_PATH = "./data/detection/" __C.TEST.SCORE_THRESHOLD = 0.25 __C.TEST.IOU_THRESHOLD = 0.5 '''

[ssimon0327tw]

Thanks a lot!

Joel Jacob @.***> 於 2022年3月30日 週三 15:46 寫道：

Hi,

I am trying to convert my custom YOLOv4 weights to TF using below command- python save_model.py --weights ./data/yolo-obj_best.weights --output ./checkpoints/yolov4-704 --input_size 704 --model yolov4

But getting below error- File "save_model.py", line 58, in app.run(main) File "/usr/local/lib/python3.6/dist-packages/absl/app.py", line 299, in run _run_main(main, args) File "/usr/local/lib/python3.6/dist-packages/absl/app.py", line 250, in _run_main sys.exit(main(argv)) File "save_model.py", line 54, in main save_tf() File "save_model.py", line 49, in save_tf utils.load_weights(model, FLAGS.weights, FLAGS.model, FLAGS.tiny) File "/content/drive/My Drive/kaggle/tensorflow-yolov4-tflite/core/utils.py", line 63, in load_weights conv_weights = conv_weights.reshape(conv_shape).transpose([2, 3, 1, 0]) ValueError: cannot reshape array of size 2048 into shape (18,1024,1,1)

I have only one class in my data/classes/obj.names file- obj.txt https://github.com/hunglc007/tensorflow-yolov4-tflite/files/4924125/obj.txt

Please suggest how to solve this error.

I was facing the same error, I checked my config file where mistakenly changed the default number of filters, the default was 32 and I changed it to 21, when I corrected that, I was able to convert the model into tensorflow. Hope this helps.

— Reply to this email directly, view it on GitHub https://github.com/hunglc007/tensorflow-yolov4-tflite/issues/147#issuecomment-1082740343, or unsubscribe https://github.com/notifications/unsubscribe-auth/ATUJXHYAG27RPRVUS66YJMTVCQBDTANCNFSM4O2KWYCA . You are receiving this because you commented.Message ID: @.***>

[eduardomoraes]

Simple solution Add the bellow code into /content/yolov4-deepsort/core/config.py ''' from easydict import EasyDict as edict

__C = edict()

Consumers can get config by: from config import cfg

cfg = __C

YOLO options

__C.YOLO = edict()

__C.YOLO.CLASSES = "./data/classes/coco.names" __C.YOLO.ANCHORS = [12,16, 19,36, 40,28, 36,75, 76,55, 72,146, 142,110, 192,243, 459,401] __C.YOLO.ANCHORS_V3 = [10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326] __C.YOLO.ANCHORS_TINY = [23,27, 37,58, 81,82, 81,82, 135,169, 344,319] __C.YOLO.STRIDES = [8, 16, 32] __C.YOLO.STRIDES_TINY = [16, 32] __C.YOLO.XYSCALE = [1.2, 1.1, 1.05] __C.YOLO.XYSCALE_TINY = [1.05, 1.05] __C.YOLO.ANCHOR_PER_SCALE = 3 __C.YOLO.IOU_LOSS_THRESH = 0.5

Train options

__C.TRAIN = edict()

__C.TRAIN.ANNOT_PATH = "./data/dataset/val2017.txt" __C.TRAIN.BATCH_SIZE = 2

__C.TRAIN.INPUT_SIZE = [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]

__C.TRAIN.INPUT_SIZE = 416 __C.TRAIN.DATA_AUG = True __C.TRAIN.LR_INIT = 1e-3 __C.TRAIN.LR_END = 1e-6 __C.TRAIN.WARMUP_EPOCHS = 2 __C.TRAIN.FISRT_STAGE_EPOCHS = 20 __C.TRAIN.SECOND_STAGE_EPOCHS = 30

TEST options

__C.TEST = edict()

__C.TEST.ANNOT_PATH = "./data/dataset/val2017.txt" __C.TEST.BATCH_SIZE = 2 __C.TEST.INPUT_SIZE = 416 __C.TEST.DATA_AUG = False __C.TEST.DECTECTED_IMAGE_PATH = "./data/detection/" __C.TEST.SCORE_THRESHOLD = 0.25 __C.TEST.IOU_THRESHOLD = 0.5 '''

Hi, thanks for the solution purposed. Still getting an error here. After applying this, the model shows the same error with different numbers. Now I have: cannot reshape array of size 28407 into shape (33,1024,1,1). I don't know what to do from here. Any help would be appreciated. Thanks

[eduardomoraes]

Hi, thanks for the solution purposed. Still getting an error here. After applying this, the model shows the same error with different numbers. Now I have: cannot reshape array of size 28407 into shape (33,1024,1,1). I don't know what to do from here. Any help would be appreciated. Thanks

[lamegaton]

Hi, thanks for the solution purposed. Still getting an error here. After applying this, the model shows the same error with different numbers. Now I have: cannot reshape array of size 28407 into shape (33,1024,1,1). I don't know what to do from here. Any help would be appreciated. Thanks

In tensorflow-yolov4-tflite, you can make a copy of data/classes/coco.names for later use. Then, overwrite your custom classes into coco.names