Output Formatting #1908
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In the tutorial notebook, the output of our model is a picture with the bounding boxes. Is there a way to get the location and size of the bounding box instead? I am trying to use it for real time navigation on a drone, so I don't want to store extra images on my small computer or waste time looking through the image for the box. |
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Replies: 1 comment 3 replies
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@Gastastrophe 👋 Hello! Thanks for asking about handling inference results. YOLOv5 🚀 PyTorch Hub models allow for simple model loading and inference in a pure python environment without using Simple Inference ExampleThis example loads a pretrained YOLOv5s model from PyTorch Hub as import torch
# Model
model = torch.hub.load('ultralytics/yolov5', 'yolov5s') # or yolov5m, yolov5l, yolov5x, etc.
# model = torch.hub.load('ultralytics/yolov5', 'custom', 'path/to/best.pt') # custom trained model
# Images
im = 'https://ultralytics.com/images/zidane.jpg' # or file, Path, URL, PIL, OpenCV, numpy, list
# Inference
results = model(im)
# Results
results.print() # or .show(), .save(), .crop(), .pandas(), etc.
results.xyxy[0] # im predictions (tensor)
results.pandas().xyxy[0] # im predictions (pandas)
# xmin ymin xmax ymax confidence class name
# 0 749.50 43.50 1148.0 704.5 0.874023 0 person
# 2 114.75 195.75 1095.0 708.0 0.624512 0 person
# 3 986.00 304.00 1028.0 420.0 0.286865 27 tie
See YOLOv5 PyTorch Hub Tutorial for details. Good luck 🍀 and let us know if you have any other questions! |
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@glenn-jocher This works great! As one last follow up, is there a version of the custom that works with ".wts" files? The model I want to deploy is a yolov3 model saved in the wts format. EDIT: I also have it saved in the Darknet ".weights" format if that is better |
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@Gastastrophe sorry I've never heard of the wts format, and we no longer support the older darknet format (deprecated). I would recommend YOLOv5 which officially supports 11 different formats for not just inference but also validation (for getting your exported model mAP). See ultralytics/yolov5#251 FormatsYOLOv5 inference is officially supported in 11 formats:
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Alright, thank you for the help. I will have to retrain the model in one of those formats I guess. |
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@Gastastrophe 👋 Hello! Thanks for asking about handling inference results. YOLOv5 🚀 PyTorch Hub models allow for simple model loading and inference in a pure python environment without using
detect.py.Simple Inference Example
This example loads a pretrained YOLOv5s model from PyTorch Hub as
modeland passes an image for inference.'yolov5s'is the YOLOv5 'small' model. For details on all available models please see the README. Custom models can also be loaded, including custom trained PyTorch models and their exported variants, i.e. ONNX, TensorRT, TensorFlow, OpenVINO YOLOv5 models.