training problem

[SiwarRziguiING3]

j'essaye d'entrainer ma propre base de données mais j'ai obtenue cette erreur:
FileNotFoundError: [Errno 2] No such file or directory: '/content/yolov5/data/images/bus.jpg'

[SiwarRziguiING3]

Je veux dire que j'ai cette erreur après avoir supprimé l'image 'ziden.jpg et bus.jpg' dans : /content/yolov5/data/images

[glenn-jocher]

👋 hi, thanks for letting us know about this possible problem with YOLOv5 🚀. We've created a few short guidelines below to help users provide what we need in order to start investigating a possible problem.

How to create a Minimal, Reproducible Example

When asking a question, people will be better able to provide help if you provide code that they can easily understand and use to reproduce the problem. This is referred to by community members as creating a minimum reproducible example. Your code that reproduces the problem should be:

• ✅ Minimal – Use as little code as possible to produce the problem
• ✅ Complete – Provide all parts someone else needs to reproduce the problem
• ✅ Reproducible – Test the code you're about to provide to make sure it reproduces the problem

For Ultralytics to provide assistance your code should also be:

• ✅ Current – Verify that your code is up-to-date with GitHub master, and if necessary git pull or git clone a new copy to ensure your problem has not already been solved in master.
• ✅ Unmodified – Your problem must be reproducible using official YOLOv5 code without changes. Ultralytics does not provide support for custom code ⚠️.

If you believe your problem meets all the above criteria, please close this issue and raise a new one using the 🐛 Bug Report template with a minimum reproducible example to help us better understand and diagnose your problem.

Thank you! 😃

[SiwarRziguiING3]

mon code est:
!python train.py --img 640 --batch 64 --epochs 90 --data custom.yaml --weights yolov5s.pt --cache --workers 2
avec custom.yml path sont :
path: ../yolov5/data/data2
train: images/train # train images (relative to 'path')
val: images/test # val images (relative to 'path')
lors de l'execution j'ai cette erreur:
train: weights=yolov5s.pt, cfg=, data=custom.yaml, hyp=data/hyps/hyp.scratch-low.yaml, epochs=90, batch_size=64, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=ram, image_weights=False, device=, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=2, project=runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
github: up to date with https://github.com/ultralytics/yolov5 ✅
YOLOv5 🚀 v6.1-211-gcee5959 Python-3.7.13 torch-1.8.2+cu111 CUDA:0 (Tesla T4, 15110MiB)

hyperparameters: lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.5, cls_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs (RECOMMENDED)
TensorBoard: Start with 'tensorboard --logdir runs/train', view at http://localhost:6006/
Overriding model.yaml nc=80 with nc=6

             from  n    params  module                                  arguments                     

0 -1 1 3520 models.common.Conv [3, 32, 6, 2, 2]
1 -1 1 18560 models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 models.common.C3 [64, 64, 1]
3 -1 1 73984 models.common.Conv [64, 128, 3, 2]
4 -1 2 115712 models.common.C3 [128, 128, 2]
5 -1 1 295424 models.common.Conv [128, 256, 3, 2]
6 -1 3 625152 models.common.C3 [256, 256, 3]
7 -1 1 1180672 models.common.Conv [256, 512, 3, 2]
8 -1 1 1182720 models.common.C3 [512, 512, 1]
9 -1 1 656896 models.common.SPPF [512, 512, 5]
10 -1 1 131584 models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 models.common.Concat [1]
13 -1 1 361984 models.common.C3 [512, 256, 1, False]
14 -1 1 33024 models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 models.common.Concat [1]
17 -1 1 90880 models.common.C3 [256, 128, 1, False]
18 -1 1 147712 models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 models.common.Concat [1]
20 -1 1 296448 models.common.C3 [256, 256, 1, False]
21 -1 1 590336 models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 models.common.Concat [1]
23 -1 1 1182720 models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 29667 models.yolo.Detect [6, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
Model summary: 270 layers, 7035811 parameters, 7035811 gradients, 15.9 GFLOPs

Transferred 343/349 items from yolov5s.pt
Traceback (most recent call last):
File "train.py", line 670, in
main(opt)
File "train.py", line 565, in main
train(opt.hyp, opt, device, callbacks)
File "train.py", line 128, in train
amp = check_amp(model) # check AMP
File "/content/yolov5/utils/general.py", line 514, in check_amp
im = cv2.imread(ROOT / 'data' / 'images' / 'bus.jpg')[..., ::-1] # OpenCV image (BGR to RGB)
File "/content/yolov5/utils/general.py", line 989, in imread
return cv2.imdecode(np.fromfile(path, np.uint8), flags)
FileNotFoundError: [Errno 2] No such file or directory: '/content/yolov5/data/images/bus.jpg'

[glenn-jocher]

@SiwarRziguiING3 got it. It appears you've deleted bus.jpg from your data/images directory. This image is used to test AMP functionality. I'll make a PR to pull this image from our website if it's missing.

[SiwarRziguiING3]

il existe 2 images ziden.jpg et bus.jpg
quel est le rôle img ziden.jpg et est-il possible de modifier ces deux images par ma base de données ?

[glenn-jocher]

@SiwarRziguiING3 good news 😃! Your original issue may now be fixed ✅ in PR #7931. This PR uses an online bus.jpg image as a backup incase a local bus.jpg is not found during AMP checks.

To receive this update:

• Git – git pull from within your yolov5/ directory or git clone https://github.com/ultralytics/yolov5 again
• PyTorch Hub – Force-reload model = torch.hub.load('ultralytics/yolov5', 'yolov5s', force_reload=True)
• Notebooks – View updated notebooks
• Docker – sudo docker pull ultralytics/yolov5:latest to update your image

Thank you for spotting this issue and informing us of the problem. Please let us know if this update resolves the issue for you, and feel free to inform us of any other issues you discover or feature requests that come to mind. Happy trainings with YOLOv5 🚀!

[SiwarRziguiING3]

merci beaucoup