Upload 5 files

app.py

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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)

best.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7abb1d7c7e8caece6282a8f0e3d5731fc21153e01e968f8a29f703c423f8d8fb
+size 14744462

requirements.txt

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+gradio
+pandas
+
+# YOLOv5 requirements
+matplotlib>=3.2.2
+numpy>=1.18.5
+opencv-python>=4.1.1
+Pillow>=7.1.2
+PyYAML>=5.3.1
+requests>=2.23.0
+scipy>=1.4.1
+torch>=1.7.0
+torchvision>=0.8.1
+tqdm>=4.64.0
+seaborn>=0.11.0
+
+# Extras --------------------------------------
+ipython  # interactive notebook
+psutil  # system utilization
+thop>=0.1.1  # FLOPs computation