Running on google colab not detecting any car on test directory provided after fixing issue for running using python 3
santhoshnumberone opened this issue · comments
I changed the code from python 2 to python 3 using 2to3
2to3 -w filename.py
Changed weights also in vehicle-detection.py line 28 and license-plate-ocr.py line 28
according to ArgumentError in darknet.py after fixing syntax error #241
When i run bash run.sh -i samples/test -o /tmp/output -c /tmp/output/results.csv
I get no detection for car, I get his out
layer filters size input output
0 conv 32 3 x 3 / 1 416 x 416 x 3 -> 416 x 416 x 32 0.299 BFLOPs
1 max 2 x 2 / 2 416 x 416 x 32 -> 208 x 208 x 32
2 conv 64 3 x 3 / 1 208 x 208 x 32 -> 208 x 208 x 64 1.595 BFLOPs
3 max 2 x 2 / 2 208 x 208 x 64 -> 104 x 104 x 64
4 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128 1.595 BFLOPs
5 conv 64 1 x 1 / 1 104 x 104 x 128 -> 104 x 104 x 64 0.177 BFLOPs
6 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128 1.595 BFLOPs
7 max 2 x 2 / 2 104 x 104 x 128 -> 52 x 52 x 128
8 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs
9 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs
10 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs
11 max 2 x 2 / 2 52 x 52 x 256 -> 26 x 26 x 256
12 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs
13 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs
14 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs
15 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs
16 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs
17 max 2 x 2 / 2 26 x 26 x 512 -> 13 x 13 x 512
18 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs
19 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs
20 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs
21 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs
22 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs
23 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024 3.190 BFLOPs
24 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024 3.190 BFLOPs
25 route 16
26 conv 64 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 64 0.044 BFLOPs
27 reorg / 2 26 x 26 x 64 -> 13 x 13 x 256
28 route 27 24
29 conv 1024 3 x 3 / 1 13 x 13 x1280 -> 13 x 13 x1024 3.987 BFLOPs
30 conv 125 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 125 0.043 BFLOPs
31 detection
mask_scale: Using default '1.000000'
Loading weights from data/vehicle-detector/yolo-voc.weights...Done!
Searching for vehicles using YOLO...
Scanning samples/test/03009.jpg
0 cars found
Scanning samples/test/03016.jpg
0 cars found
Scanning samples/test/03025.jpg
0 cars found
Scanning samples/test/03033.jpg
0 cars found
Scanning samples/test/03057.jpg
0 cars found
Scanning samples/test/03058.jpg
0 cars found
Scanning samples/test/03066.jpg
0 cars found
Scanning samples/test/03071.jpg
0 cars found
2022-02-15 16:50:37.204997: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.
Searching for license plates using WPOD-NET
layer filters size input output
0 conv 32 3 x 3 / 1 240 x 80 x 3 -> 240 x 80 x 32 0.033 BFLOPs
1 max 2 x 2 / 2 240 x 80 x 32 -> 120 x 40 x 32
2 conv 64 3 x 3 / 1 120 x 40 x 32 -> 120 x 40 x 64 0.177 BFLOPs
3 max 2 x 2 / 2 120 x 40 x 64 -> 60 x 20 x 64
4 conv 128 3 x 3 / 1 60 x 20 x 64 -> 60 x 20 x 128 0.177 BFLOPs
5 conv 64 1 x 1 / 1 60 x 20 x 128 -> 60 x 20 x 64 0.020 BFLOPs
6 conv 128 3 x 3 / 1 60 x 20 x 64 -> 60 x 20 x 128 0.177 BFLOPs
7 max 2 x 2 / 2 60 x 20 x 128 -> 30 x 10 x 128
8 conv 256 3 x 3 / 1 30 x 10 x 128 -> 30 x 10 x 256 0.177 BFLOPs
9 conv 128 1 x 1 / 1 30 x 10 x 256 -> 30 x 10 x 128 0.020 BFLOPs
10 conv 256 3 x 3 / 1 30 x 10 x 128 -> 30 x 10 x 256 0.177 BFLOPs
11 conv 512 3 x 3 / 1 30 x 10 x 256 -> 30 x 10 x 512 0.708 BFLOPs
12 conv 256 3 x 3 / 1 30 x 10 x 512 -> 30 x 10 x 256 0.708 BFLOPs
13 conv 512 3 x 3 / 1 30 x 10 x 256 -> 30 x 10 x 512 0.708 BFLOPs
14 conv 80 1 x 1 / 1 30 x 10 x 512 -> 30 x 10 x 80 0.025 BFLOPs
15 detection
mask_scale: Using default '1.000000'
Loading weights from data/ocr/ocr-net.weights...Done!
Performing OCR...
rm: cannot remove '/tmp/output/*_lp.png': No such file or directory
---------------------------------------------------------------------------
CalledProcessError Traceback (most recent call last)
[<ipython-input-5-301d792980f0>](https://localhost:8080/#) in <module>()
----> 1 get_ipython().run_cell_magic('shell', '', '\nbash run.sh -i samples/test -o /tmp/output -c /tmp/output/results.csv')
2 frames
[/usr/local/lib/python3.7/dist-packages/google/colab/_system_commands.py](https://localhost:8080/#) in check_returncode(self)
137 if self.returncode:
138 raise subprocess.CalledProcessError(
--> 139 returncode=self.returncode, cmd=self.args, output=self.output)
140
141 def _repr_pretty_(self, p, cycle): # pylint:disable=unused-argument
CalledProcessError: Command '
bash run.sh -i samples/test -o /tmp/output -c /tmp/output/results.csv' returned non-zero exit status 1.
What is going wrong here?
i have the same problem!!!
Hello! I am having the same issue. Did you find the solution?
+1
Hi,
This problem was solved in the closed issue #25 (comment)
Hope this helps!
I changed the code from python 2 to python 3 using
2to3
2to3 -w filename.pyChanged weights also in
vehicle-detection.pyline28andlicense-plate-ocr.pyline28according to ArgumentError in darknet.py after fixing syntax error #241When i run
bash run.sh -i samples/test -o /tmp/output -c /tmp/output/results.csvI get no detection for car, I get his out
layer filters size input output 0 conv 32 3 x 3 / 1 416 x 416 x 3 -> 416 x 416 x 32 0.299 BFLOPs 1 max 2 x 2 / 2 416 x 416 x 32 -> 208 x 208 x 32 2 conv 64 3 x 3 / 1 208 x 208 x 32 -> 208 x 208 x 64 1.595 BFLOPs 3 max 2 x 2 / 2 208 x 208 x 64 -> 104 x 104 x 64 4 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128 1.595 BFLOPs 5 conv 64 1 x 1 / 1 104 x 104 x 128 -> 104 x 104 x 64 0.177 BFLOPs 6 conv 128 3 x 3 / 1 104 x 104 x 64 -> 104 x 104 x 128 1.595 BFLOPs 7 max 2 x 2 / 2 104 x 104 x 128 -> 52 x 52 x 128 8 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 9 conv 128 1 x 1 / 1 52 x 52 x 256 -> 52 x 52 x 128 0.177 BFLOPs 10 conv 256 3 x 3 / 1 52 x 52 x 128 -> 52 x 52 x 256 1.595 BFLOPs 11 max 2 x 2 / 2 52 x 52 x 256 -> 26 x 26 x 256 12 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 13 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 14 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 15 conv 256 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 256 0.177 BFLOPs 16 conv 512 3 x 3 / 1 26 x 26 x 256 -> 26 x 26 x 512 1.595 BFLOPs 17 max 2 x 2 / 2 26 x 26 x 512 -> 13 x 13 x 512 18 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs 19 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs 20 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs 21 conv 512 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 512 0.177 BFLOPs 22 conv 1024 3 x 3 / 1 13 x 13 x 512 -> 13 x 13 x1024 1.595 BFLOPs 23 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024 3.190 BFLOPs 24 conv 1024 3 x 3 / 1 13 x 13 x1024 -> 13 x 13 x1024 3.190 BFLOPs 25 route 16 26 conv 64 1 x 1 / 1 26 x 26 x 512 -> 26 x 26 x 64 0.044 BFLOPs 27 reorg / 2 26 x 26 x 64 -> 13 x 13 x 256 28 route 27 24 29 conv 1024 3 x 3 / 1 13 x 13 x1280 -> 13 x 13 x1024 3.987 BFLOPs 30 conv 125 1 x 1 / 1 13 x 13 x1024 -> 13 x 13 x 125 0.043 BFLOPs 31 detection mask_scale: Using default '1.000000' Loading weights from data/vehicle-detector/yolo-voc.weights...Done! Searching for vehicles using YOLO... Scanning samples/test/03009.jpg 0 cars found Scanning samples/test/03016.jpg 0 cars found Scanning samples/test/03025.jpg 0 cars found Scanning samples/test/03033.jpg 0 cars found Scanning samples/test/03057.jpg 0 cars found Scanning samples/test/03058.jpg 0 cars found Scanning samples/test/03066.jpg 0 cars found Scanning samples/test/03071.jpg 0 cars found 2022-02-15 16:50:37.204997: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0. Searching for license plates using WPOD-NET layer filters size input output 0 conv 32 3 x 3 / 1 240 x 80 x 3 -> 240 x 80 x 32 0.033 BFLOPs 1 max 2 x 2 / 2 240 x 80 x 32 -> 120 x 40 x 32 2 conv 64 3 x 3 / 1 120 x 40 x 32 -> 120 x 40 x 64 0.177 BFLOPs 3 max 2 x 2 / 2 120 x 40 x 64 -> 60 x 20 x 64 4 conv 128 3 x 3 / 1 60 x 20 x 64 -> 60 x 20 x 128 0.177 BFLOPs 5 conv 64 1 x 1 / 1 60 x 20 x 128 -> 60 x 20 x 64 0.020 BFLOPs 6 conv 128 3 x 3 / 1 60 x 20 x 64 -> 60 x 20 x 128 0.177 BFLOPs 7 max 2 x 2 / 2 60 x 20 x 128 -> 30 x 10 x 128 8 conv 256 3 x 3 / 1 30 x 10 x 128 -> 30 x 10 x 256 0.177 BFLOPs 9 conv 128 1 x 1 / 1 30 x 10 x 256 -> 30 x 10 x 128 0.020 BFLOPs 10 conv 256 3 x 3 / 1 30 x 10 x 128 -> 30 x 10 x 256 0.177 BFLOPs 11 conv 512 3 x 3 / 1 30 x 10 x 256 -> 30 x 10 x 512 0.708 BFLOPs 12 conv 256 3 x 3 / 1 30 x 10 x 512 -> 30 x 10 x 256 0.708 BFLOPs 13 conv 512 3 x 3 / 1 30 x 10 x 256 -> 30 x 10 x 512 0.708 BFLOPs 14 conv 80 1 x 1 / 1 30 x 10 x 512 -> 30 x 10 x 80 0.025 BFLOPs 15 detection mask_scale: Using default '1.000000' Loading weights from data/ocr/ocr-net.weights...Done! Performing OCR... rm: cannot remove '/tmp/output/*_lp.png': No such file or directory --------------------------------------------------------------------------- CalledProcessError Traceback (most recent call last) [<ipython-input-5-301d792980f0>](https://localhost:8080/#) in <module>() ----> 1 get_ipython().run_cell_magic('shell', '', '\nbash run.sh -i samples/test -o /tmp/output -c /tmp/output/results.csv') 2 frames [/usr/local/lib/python3.7/dist-packages/google/colab/_system_commands.py](https://localhost:8080/#) in check_returncode(self) 137 if self.returncode: 138 raise subprocess.CalledProcessError( --> 139 returncode=self.returncode, cmd=self.args, output=self.output) 140 141 def _repr_pretty_(self, p, cycle): # pylint:disable=unused-argument CalledProcessError: Command ' bash run.sh -i samples/test -o /tmp/output -c /tmp/output/results.csv' returned non-zero exit status 1.What is going wrong here?