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This PR pushes the autoShape concept further with a Detections() class produced by YOLOv5 inference now when using .autoShape(). PyTorch Hub tutorial updated also, and we are also finalizing an official submission to https://github.com/pytorch/hub.
Everything works super simply. To see a preview simply run
$ python hubconf.py
. Example:🛠️ PR Summary
Made with ❤️ by Ultralytics Actions
🌟 Summary
Enhancements to YOLOv5 inference and image processing.
📊 Key Changes
if len(det)
instead ofif det is not None and len(det)
).pillow
.autoShape
andDetections
classes to improve image input handling, normalization, and post-processing.Detections
class to encapsulate detection results with various output functions (print, show, save).🎯 Purpose & Impact
Pillow
integration aims to enhance image operations and make the library more user-friendly for image-related tasks.Detections
class provides a standard way to interact with inference outputs, easing the display and interpretation of results for users.