how to crop images after detection in yolov5s

[harshmgoyal]

❔Question

how to take out coordinates of bounding box image after detection ? or is there any other method to crop ?

Additional context

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[cjsLindquist]

Setting the '--save-txt' argument on detect.py will output the bounding box locations and classes into /inference/output/ with one file per image. You can simply read in these files and crop the bboxes out of the appropriate images or video frames using OpenCV etc.

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This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

[shivprasad94]

https://github.com/ultralytics/yolov5/issues/2608#issuecomment-809094537

U can refer to my reply in the above link.

[burhr2]

Hi! have added the saving option of the detected objects which will be in project/name/cropped when using detect.py. I have made a PR to this repo but you can check the changes in my folk yolov5

[glenn-jocher]

@harshmgoyal @cjsLindquist Prediction box cropping is now available in YOLOv5 via PR https://github.com/ultralytics/yolov5/pull/2827! PyTorch Hub models can use results.crop() or detect.py can be called with the --save-crop argument. Example usage:

python detect.py --save-crop

[bachimanchiajay]

How to extract text from the --save-crop images having multiple classes will be saving the images in a crop folder i need the text as well for that specific cropped image can anyone help me how we can do that.

[glenn-jocher]

@bachimanchiajay 👋 Hello! Thanks for asking about cropping results with YOLOv5 🚀. Cropping bounding box detections can be useful for training classification models on box contents for example. This feature was added in PR https://github.com/ultralytics/yolov5/pull/2827. You can crop detections using either detect.py or YOLOv5 PyTorch Hub:

detect.py

Crops will be saved under runs/detect/exp/crops, with a directory for each class detected.

python detect.py --save-crop

YOLOv5 PyTorch Hub

Crops will be saved under runs/detect/exp/crops if save=True, and also returned as a dictionary with crops as numpy arrays.

import torch

# Model
model = torch.hub.load('ultralytics/yolov5', 'yolov5s')  # or yolov5m, yolov5l, yolov5x, custom

# Images
img = 'https://ultralytics.com/images/zidane.jpg'  # or file, Path, PIL, OpenCV, numpy, list

# Inference
results = model(img)

# Results
crops = results.crop(save=True) 
# -- or --
crops = results.crop(save=True, save_dir='runs/detect/exp')  # specify save dir

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

[bachimanchiajay]

I can able to see the cropped results but i have to extract text from the cropped images before cropping i have to pass these predicted coordina To the textract for ocr.

On Tue, 18 Oct 2022 at 5:25 PM, Glenn Jocher @.***> wrote:

@bachimanchiajay https://github.com/bachimanchiajay 👋 Hello! Thanks for asking about cropping results with YOLOv5 🚀. Cropping bounding box detections can be useful for training classification models on box contents for example. This feature was added in PR #2827 https://github.com/ultralytics/yolov5/pull/2827. You can crop detections using either detect.py or YOLOv5 PyTorch Hub: detect.py

Crops will be saved under runs/detect/exp/crops, with a directory for each class detected.

python detect.py --save-crop

[image: Original] https://user-images.githubusercontent.com/26833433/139577918-65cc8f5d-741d-4a88-8753-0154013c624d.jpg

[image: Crop] https://user-images.githubusercontent.com/26833433/139577896-aa26b07c-466d-4057-9bfe-b01b56007587.png YOLOv5 PyTorch Hub

Crops will be saved under runs/detect/exp/crops if save=True, and also returned as a dictionary with crops as numpy arrays.

import torch

Model

model = torch.hub.load('ultralytics/yolov5', 'yolov5s') # or yolov5m, yolov5l, yolov5x, custom

Images

img = 'https://ultralytics.com/images/zidane.jpg' # or file, Path, PIL, OpenCV, numpy, list

Inference

results = model(img)

Results

crops = results.crop(save=True)

-- or --

crops = results.crop(save=True, save_dir='runs/detect/exp') # specify save dir

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

— Reply to this email directly, view it on GitHub https://github.com/ultralytics/yolov5/issues/1028#issuecomment-1282267078, or unsubscribe https://github.com/notifications/unsubscribe-auth/AHQB7G663IDUTMWR7QSBX2DWD2F3JANCNFSM4RXYISZQ . You are receiving this because you were mentioned.Message ID: @.***>

[gobspn]

Can I change the file extension from .jpg to .png before used '--save-crop'.

[glenn-jocher]

@gobspn hello! Yes, you can change the file extension from .jpg to .png before using '--save-crop' in detect.py or results.crop(save=True) in YOLOv5 PyTorch Hub. The saved cropped images will also have the same file extension as the input images.