WARNING: Dataset not found, nonexistent paths: ['/content/valid/images']

[ghost]

I have read the previous post regarding this issue but the solution, pip install -U roboflow is not working for me.

My dataset location:

%cat /content/yolov5/data.yaml
train: ../train/images
val: ../valid/images

The taining command:

%%time
%cd /content/yolov5/
!python train.py --img 416 --batch 16 --epochs 100 --data /content/yolov5/data.yaml --cfg /content/yolov5/models/custom_yolov5s.yaml --weights '' --name yolov5s --cache

Errors:

/content/yolov5
github: ⚠️ WARNING: code is out of date by 787 commits. Use 'git pull' to update or 'git clone https://github.com/ultralytics/yolov5' to download latest.
YOLOv5 v4.0-126-g886f1c0 torch 1.10.0+cu111 CUDA:0 (Tesla T4, 15109.75MB)

Namespace(adam=False, batch_size=16, bucket='', cache_images=True, cfg='/content/yolov5/models/custom_yolov5s.yaml', data='/content/yolov5/data.yaml', device='', entity=None, epochs=100, evolve=False, exist_ok=False, global_rank=-1, hyp='data/hyp.scratch.yaml', image_weights=False, img_size=[416, 416], linear_lr=False, local_rank=-1, log_artifacts=False, log_imgs=16, multi_scale=False, name='yolov5s_fyp', noautoanchor=False, nosave=False, notest=False, project='runs/train', quad=False, rect=False, resume=False, save_dir='runs/train/yolov5s_fyp3', single_cls=False, sync_bn=False, total_batch_size=16, weights='', workers=8, world_size=1)
wandb: Install Weights & Biases for YOLOv5 logging with 'pip install wandb' (recommended)
Start Tensorboard with "tensorboard --logdir runs/train", view at http://localhost:6006/
hyperparameters: lr0=0.01, lrf=0.2, 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

WARNING: Dataset not found, nonexistent paths: ['/content/valid/images']
Traceback (most recent call last):
File "train.py", line 531, in
train(hyp, opt, device, tb_writer, wandb)
File "train.py", line 65, in train
check_dataset(data_dict) # check
File "/content/yolov5/utils/general.py", line 145, in check_dataset
raise Exception('Dataset not found.')
Exception: Dataset not found.
CPU times: user 40.7 ms, sys: 18.1 ms, total: 58.9 ms
Wall time: 5.14 s

[glenn-jocher]

@RealOne01 before you do anything you should update your code as it is out of date by almost 800 commits. Then head over to the Train Custom Data tutorial to get started:

YOLOv5 Tutorials

• Train Custom Data  🚀 RECOMMENDED
• Tips for Best Training Results  ☘️ RECOMMENDED
• Weights & Biases Logging  🌟 NEW
• Supervisely Ecosystem  🌟 NEW
• Multi-GPU Training
• PyTorch Hub  ⭐ NEW
• TFLite, ONNX, CoreML, TensorRT Export 🚀
• Test-Time Augmentation (TTA)
• Model Ensembling
• Model Pruning/Sparsity
• Hyperparameter Evolution
• Transfer Learning with Frozen Layers  ⭐ NEW
• TensorRT Deployment

Good luck 🍀 and let us know if you have any other questions!

[muhammad-faizan-122]

The issue is due to not found actual dataset path. I found same issue when i trained the Yolov5 model on custom dataset using google colab, I did the following to resolve this.

1. Make sure provide correct path of data.yaml of dataset.
2. Make sure path of dataset in data.yaml should be be corrected.
3. train, test, and valid key should contain path with respect to the main path of the dataset.
   Example data.yaml file given below.

path: /content/drive/MyDrive/car-detection-dataset
train: train/images
val: valid/images
test: test/images

nc: 1
names: ['car']

[yashika-git]

@muhammad-faizan-122, Can you please tell where should the labels for train and test images be stored?

[muhammad-faizan-122]

Dataset directory format should be following.
Dataset

• train
  • images
  • labels
• test
  • images
  • labels
• valid
  • images
  • labels

labels directory contains the txt files, each txt file contains ground truth class of object with its bounding boxes parameters. The name of the image in images directory and its label in labels directory must be same.

[yashika-git]

Thanks @muhammad-faizan-122, the data.yaml file should also be in the Dataset folder?

[muhammad-faizan-122]

Yes.

[jiminpopo]

I change the path of dataset in data.yaml file. It works well

[rosevpattani]

The same problem with me too in yolov7.

WARNING: Dataset not found, nonexistent paths: ['/content/gdrive/MyDrive/Object/yolov7/content/gdrive/MyDrive/Object/yolov7/data/val/img']
Traceback (most recent call last):
File "train.py", line 616, in
train(hyp, opt, device, tb_writer)
File "train.py", line 97, in train
check_dataset(data_dict) # check
File "/content/gdrive/MyDrive/Object/yolov7/utils/general.py", line 173, in check_dataset
raise Exception('Dataset not found.')
Exception: Dataset not found.

Please give me suggestions

[yashika-git]

I resolved the issue by using absolute paths instead of relative paths and also by switching the type of slash (forward or backward) I was using in the path.

[kuan79223]

我也有相同的問題

[15ihsanmuttaqin]

I'm also facing the same problem as you, has someone found a solution?

[kuan79223]

solution: re-download the author's package

[rajat1425]

i also facing the same issue on kaggle. Can anyone guide me how to resolve it?

[cbru241]

I encountered the same issue, but I resolved it by changing the dataset download from YOLOv5 Oriented Bounding Boxes to YOLO v5 PyTorch one PyTorch. Maybe this will help someone in the future :)

[jpinzonc]

I am having the same issue, but the paths are correct. I have tried all the combinations above with no luck. I am using Google Colab.

[jpinzonc]

I fix it by editing the path inside the .yaml file, from:

test: ../test/images
train: SoccerBallDetect-7/train/images
val: SoccerBallDetect-7/valid/images

to:

test: ../test/images
train: /content/SoccerBallDetect-7/train/images
val: /content/SoccerBallDetect-7/valid/images

[rutchaphon123]

Change directory in data.yaml by double click and Ctrl + S to save. It work for me.