opencv-for-darknet
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Published
20 hours ago •
chineseocr
chineseocr
help, Unsupported activation: relu in function 'ReadDarknetFromCfgStream'
cv2.error: OpenCV(4.0.1) /root/ocr/opencv-4.0.1/modules/dnn/src/darknet/darknet_io.cpp:552: error: (-212:Parsing error) Unsupported activation: relu in function 'ReadDarknetFromCfgStream'
@x931890193 I have the same problem, so did u solved it ?
hey, I run in jetson nano, this my env.
(camera) [email protected] /data/ocr/darknet-ocr$ python app.py
learning_rate: Using default '0.001000'
momentum: Using default '0.900000'
policy: Using default 'constant'
max_batches: Using default '0'
layer filters size input output
0 conv 64 3 x 3 / 1 256 x 32 x 1 -> 256 x 32 x 64 0.009 BFLOPs
1 max 2 x 2 / 2 x 2 256 x 32 x 64 -> 128 x 16 x 64
2 conv 128 3 x 3 / 1 128 x 16 x 64 -> 128 x 16 x 128 0.302 BFLOPs
3 max 2 x 2 / 2 x 2 128 x 16 x 128 -> 64 x 8 x 128
4 conv 256 3 x 3 / 1 64 x 8 x 128 -> 64 x 8 x 256 0.302 BFLOPs
5 conv 256 3 x 3 / 1 64 x 8 x 256 -> 64 x 8 x 256 0.604 BFLOPs
6 max 2 x 2 / 2 x 1 64 x 8 x 256 -> 63 x 4 x 256
Unused field: 'strideW = 1'
Unused field: 'strideH = 2'
7 conv 512 3 x 3 / 1 63 x 4 x 256 -> 63 x 4 x 512 0.595 BFLOPs
8 conv 512 3 x 3 / 1 63 x 4 x 512 -> 63 x 4 x 512 1.189 BFLOPs
9 max 2 x 2 / 2 x 1 63 x 4 x 512 -> 62 x 2 x 512
Unused field: 'strideW = 1'
Unused field: 'strideH = 2'
10 conv 512 2 x 2 / 1 62 x 2 x 512 -> 61 x 1 x 512 0.128 BFLOPs
11 conv 11316 1 x 1 / 1 61 x 1 x 512 -> 61 x 1 x11316 0.707 BFLOPs
Loading weights from models/ocr/chinese/ocr.weights...Done!
learning_rate: Using default '0.001000'
momentum: Using default '0.900000'
policy: Using default 'constant'
max_batches: Using default '0'
layer filters size input output
0 conv 64 3 x 3 / 1 32 x 32 x 3 -> 32 x 32 x 64 0.004 BFLOPs
1 conv 64 3 x 3 / 1 32 x 32 x 64 -> 32 x 32 x 64 0.075 BFLOPs
2 max 2 x 2 / 2 x 2 32 x 32 x 64 -> 16 x 16 x 64
3 conv 128 3 x 3 / 1 16 x 16 x 64 -> 16 x 16 x 128 0.038 BFLOPs
4 conv 128 3 x 3 / 1 16 x 16 x 128 -> 16 x 16 x 128 0.075 BFLOPs
5 max 2 x 2 / 2 x 2 16 x 16 x 128 -> 8 x 8 x 128
6 conv 256 3 x 3 / 1 8 x 8 x 128 -> 8 x 8 x 256 0.038 BFLOPs
7 conv 256 3 x 3 / 1 8 x 8 x 256 -> 8 x 8 x 256 0.075 BFLOPs
8 conv 256 3 x 3 / 1 8 x 8 x 256 -> 8 x 8 x 256 0.075 BFLOPs
9 max 2 x 2 / 2 x 2 8 x 8 x 256 -> 4 x 4 x 256
10 conv 512 3 x 3 / 1 4 x 4 x 256 -> 4 x 4 x 512 0.038 BFLOPs
11 conv 512 3 x 3 / 1 4 x 4 x 512 -> 4 x 4 x 512 0.075 BFLOPs
12 conv 512 3 x 3 / 1 4 x 4 x 512 -> 4 x 4 x 512 0.075 BFLOPs
13 max 2 x 2 / 2 x 2 4 x 4 x 512 -> 2 x 2 x 512
14 conv 512 3 x 3 / 1 2 x 2 x 512 -> 2 x 2 x 512 0.019 BFLOPs
15 conv 512 3 x 3 / 1 2 x 2 x 512 -> 2 x 2 x 512 0.019 BFLOPs
16 conv 512 3 x 3 / 1 2 x 2 x 512 -> 2 x 2 x 512 0.019 BFLOPs
17 conv 512 3 x 3 / 1 2 x 2 x 512 -> 2 x 2 x 512 0.019 BFLOPs
18 conv 40 1 x 1 / 1 2 x 2 x 512 -> 2 x 2 x 40 0.000 BFLOPs
Loading weights from models/text/text.weights...Done!
http://0.0.0.0:8080/
env:
^C^C(camera) [email protected] /data/ocr/darknet-ocr$
(camera) [email protected] /data/ocr/darknet-ocr$ python
Python 3.6.9 (default, Apr 18 2020, 01:56:04)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import cv2
>>> cv2.__version__
'4.1.1'
>>>