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""" | |
Source: https://github.com/AK391/yolov5/blob/master/utils/gradio/demo.py | |
""" | |
import gradio as gr | |
import torch | |
from PIL import Image | |
model = torch.hub.load('ultralytics/yolov5', 'custom', 'best.pt') # force_reload=True to update | |
def yolo(im, size=640): | |
g = (size / max(im.size)) # gain | |
im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS) # resize | |
results = model(im) # inference | |
results.render() # updates results.ims with boxes and labels | |
return Image.fromarray(results.ims[0]) | |
inputs = gr.inputs.Image(type='pil', label="Original Image") | |
outputs = gr.outputs.Image(type="pil", label="Output Image") | |
title = "YOLOv5" | |
description = "YOLOv5 demo for fire detection. Upload an image or click an example image to use." | |
article = "See https://github.com/robmarkcole/fire-detection-from-images" | |
examples = [['pan-fire.jpg'], ['fire-basket.jpg']] | |
gr.Interface(yolo, inputs, outputs, title=title, description=description, article=article, examples=examples).launch( | |
debug=True) |