yolov3-channel-and-layer-pruning
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tanluren
ValueError: need at least one array to concatenate
I am having this error since two days. i tried everything but dont know how to solve it.please kindly reply
labels4 = np.concatenate(labels4, 0) File "<array_function internals>", line 6, in concatenate
Samples are available？numpy？
Samples are available. but there are some labels that are empty because I use only 2 classes in the Pascal VOC dataset. ] also, i just put mosiac as false because this error occurs in mosiac file which collects 4 images for training.
If there are empty labels，https://github.com/tanluren/yolov3-channel-and-layer-pruning/blob/master/utils/datasets.py#L591 Uncomment
Thank you so much for helping.
I have another problem too!! when i finish training in evaluation step i the mAP is zero because i don't have .json file for VOC evaluation set. How can i evaluate my evaluation set? Do you have any idea.
https://github.com/ultralytics/yolov3/wiki/Train-Custom-Data https://blog.csdn.net/qq_34795071/article/details/90769094
https://github.com/ultralytics/yolov3/wiki/Train-Custom-Data https://blog.csdn.net/qq_34795071/article/details/90769094
Thank you so much. i am using both of these tutorials but I don't know I have errors in evaluation. maybe because in evaluation it class the coco instances2014.json.
https://github.com/ultralytics/yolov3/wiki/Train-Custom-Data https://blog.csdn.net/qq_34795071/article/details/90769094
I have the following error in the evaluation of the validation set. Note I am using thevoc dataset. Starting training for 10 epochs...
Epoch gpu_mem GIoU obj cls total soft rratio targets img_size
0%| | 0/1355 [00:00<?, ?it/s]learning rate: 1e-06
0/9 7.65G 2.31 1.78 44.8 48.9 0 0 3 416: 100%|█████████████████████████████████████████████████████████████████████████████████████████████| 1355/1355 [15:19<00:00, 1.47it/s]
Reading image shapes: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5417/5417 [00:20<00:00, 265.06it/s]
Class Images Targets P R mAP F1: 0%| | 0/339 [00:00<?, ?it/s]Traceback (most recent call last):
File "
File "train.py", line 418, in train
_fixup_main_from_path(data['init_main_from_path'])
File "C:\Users\power703\Anaconda3\lib\multiprocessing\spawn.py", line 277, in _fixup_main_from_path
save_json=final_epoch and epoch > 0 and 'fruit.data' in data)
File "C:\Users\power703\Desktop\incdet\yolov3-channel-and-layer-pruning\test.py", line 64, in test
run_name="mp_main")
File "C:\Users\power703\Anaconda3\lib\runpy.py", line 263, in run_path
for batch_i, (imgs, targets, paths, shapes) in enumerate(tqdm(dataloader, desc=s)):
File "C:\Users\power703\Anaconda3\lib\site-packages\tqdm\std.py", line 1129, in iter
pkg_name=pkg_name, script_name=fname)
File "C:\Users\power703\Anaconda3\lib\runpy.py", line 96, in _run_module_code
mod_name, mod_spec, pkg_name, script_name)
File "C:\Users\power703\Anaconda3\lib\runpy.py", line 85, in run_code
exec(code, run_globals)
File "C:\Users\power703\Desktop\incdet\yolov3-channel-and-layer-pruning\train.py", line 3, in
I also want to ask how big your graphics card is and how much batch size is set.
My graphics card is GPU is 1080 and batch size is i tried 16 and 4 and 2 and 8
It is estimated that the environment problem, the version of python numpy torch does not match, it is recommended to try another version
Which version od python nmpy and torch should i use. I tried the requirement.txt file which was having some error and i installed ..
Python 3.6.7 absl-py 0.8.0 albumentations 0.3.3 apex 0.1 asn1crypto 1.2.0 astor 0.8.0 backcall 0.1.0 certifi 2019.9.11 cffi 1.13.2 chardet 3.0.4 colorama 0.4.1 cryptography 2.7 cycler 0.10.0 Cython 0.29.14 decorator 4.4.1 future 0.18.1 gast 0.2.2 gevent 1.4.0 google-pasta 0.1.7 greenlet 0.4.15 grpcio 1.24.1 h5py 2.10.0 idna 2.8 imageio 2.6.0 imgaug 0.2.6 ipykernel 5.1.3 ipython 7.9.0 ipython-genutils 0.2.0 jedi 0.15.1 jupyter-client 5.3.3 jupyter-core 4.5.0 Keras 2.3.1 Keras-Applications 1.0.8 Keras-Preprocessing 1.1.0 keras-resnet 0.1.0 keras-retinanet 0.5.1 kiwisolver 1.1.0 labelImg 1.8.3 lxml 4.5.0 Markdown 3.1.1 matplotlib 3.1.1 networkx 2.3 numpy 1.17.3 olefile 0.46 opencv-python-headless 4.1.1.26 opt-einsum 3.1.0 pandas 1.0.1 parso 0.5.1 pickleshare 0.7.5 Pillow 6.2.1 pip 19.2.3 progressbar2 3.47.0 prompt-toolkit 2.0.10 protobuf 3.10.0 pycocotools 2.0 pycparser 2.19 Pygments 2.4.2 pyOpenSSL 19.0.0 pyparsing 2.4.5 PyQt5 5.14.1 PyQt5-sip 12.7.1 PySocks 1.7.1 pytesseract 0.3.2 python-dateutil 2.8.1 python-utils 2.3.0 pytz 2019.3 PyWavelets 1.0.3 pywin32 225 PyYAML 5.1.2 pyzmq 18.1.0 requests 2.22.0 scikit-image 0.15.0 scipy 1.3.2 setuptools 41.2.0 six 1.12.0 tensorboard 2.0.0 tensorboardX 1.9 tensorflow 2.0.0 tensorflow-estimator 2.0.0 termcolor 1.1.0 terminaltables 3.1.0 torch 1.2.0 torchfile 0.1.0 torchvision 0.4.0 tornado 6.0.3 tqdm 4.36.1 traitlets 4.3.3 urllib3 1.25.6 visdom 0.1.8.9 wcwidth 0.1.7 webcolors 1.11.1 websocket-client 0.56.0 Werkzeug 0.16.0 wheel 0.33.6 win-inet-pton 1.1.0 wincertstore 0.2 wrapt 1.11.1
this is mine, you can select and install the pkg you need
Thank you so much.. Basically i want to use the distillation knowledge in yolov3. Can you point out the code that is only used for the distillation network..
https://github.com/tanluren/yolov3-channel-and-layer-pruning/blob/master/train.py#L366
