<jupyter_start><jupyter_text>1er étape:Vérifier la carte graphique utilisé par votre google collab (si pas de carte graphique,changer le mode d'execution en GPU dans l'onglet execution) On repere par exemple ici qu'il s'agit d'une Tesla K80.https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/ Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. ||                               |                      |               MIG M. ||===============================+======================+======================||   0  Tesla K80           Off  | 00000000:00:04.0 Off |                    0 || N/A   35C    P8    28W / 149W |      0MiB / 11441MiB |      0%      Default ||                               |                      |                  N/A |+-------------------------------+----------------------+----------------------+<jupyter_code>!nvidia-smi<jupyter_output>Wed Oct 20 10:21:28 2021       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.74       Driver Version: 460.32.03    CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla K80           Off  | 00000000:00:04.0 Off |                    0 |
| N/A   36C    P8    28W / 149W |      0MiB / 11441MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-------[...]<jupyter_text>Si usage de google drive :<jupyter_code>#from google.colab import drive
#drive.mount('/content/gdrive')


#!ln -s /content/gdrive/MyDrive/darknet/darknet /darknet

#%cd /darknet
!ls<jupyter_output><empty_output><jupyter_text>Si usage github :<jupyter_code>!git clone https://github.com/fabricejumel/darknet
%cd darknet
!git checkout feature/google-colab
!make
#!wget https://pjreddie.com/media/files/yolov3.weights
#import darknet
#print(darknet.performDetect())
#!./darknet detector test ./cfg/coco.data ./cfg/yolov3.cfg ./yolov3.weights data/dog.jpg -i 0 -thresh 0.25
!./darknet detector test ./cfg/coco.data ./cfg/yolov3-tiny.cfg ./yolov3-tiny.weights data/dog.jpg -i 0 -thresh 0.25
#!./darknet detector test ycb.data /darknet/YOLOV3_YCB_tiny/yolov3-tiny-ycb.cfg /darknet/backup/yolov3-tiny-ycb-training_1000.weights ycb-test.jpg -i 0 -thresh 0.01
#!./darknet detector test ycb.data /darknet/YOLOV3_YCB_tiny/yolov3-tiny-ycb.cfg ./backup/yolov3-tiny-ycb.weights ycb-test.jpg -i 0 -thresh 0.25

#!./darknet detector train  ycb.data  /darknet/YOLOV3_YCB_tiny/yolov3-tiny-ycb-training.cfg yolov3-tiny.conv.15 -dont_show
#!./darknet detector train  ycb.data  /darknet/YOLOV3_YCB_tiny/yolov3-tiny-ycb-training.cfg backup/yolov3-tiny-ycb-training_9000.weights -dont_show

#!./darknet detector train  ycb.data  /darknet/YOLOV3_YCB_tiny/yolov3-tiny-ycb-training.cfg yolov3-tiny.conv.15 -dont_show
#!./darknet partial cfg/yolov3-tiny.cfg yolov3-tiny.weights yolov3-tiny.conv.15 15<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.24004649811101425, 'fraction_numerical': 0.04330136588201104, 'mean_word_length': 1.6436251920122888, 'pattern_counts': {'":': 0, '<': 12, '<?xml version=': 0, '>': 12, 'https://': 3, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 2, 'word_list_counts': {'cursed_substrings.json': 15, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '422530', 'license': 'Unlicense', 'n_tokens_mistral': 1229, 'n_tokens_neox': 1100, 'n_words': 212, 'path': 'test_darknet_robia_collab.ipynb', 'repo_name': 'fabricejumel/darknet_collab', 'size': '3441'}