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import gradio as gr |
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import cv2 |
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import requests |
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import os |
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from ultralytics import YOLO |
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path = ['./data/0068.jpg', './data/0210.jpg', './data/IMG_7078.jpg', './data/IMG_7103.jpg', './data/IMG_7705.jpg'] |
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model_path = './best.pt' |
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model = YOLO(model_path) |
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def detect_cheerios(image_path): |
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results = model(image_path) |
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image = results[0].plot() [:,:,::-1] |
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return image |
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iface = gr.Interface( |
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fn=detect_cheerios, |
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inputs=gr.components.Image(type="filepath", label="Input Image"), |
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outputs=gr.Image(), |
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title="Cheerios detector", |
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description='Duality.ai offers a free simulation software where you can create large datasets right from your computer. Used by companies like P&G, KEF Robotics, and AWS, this powerful software is now available for non-commercial use. Go to <a href="https://falcon.duality.ai/secure/documentation?learnWelcome=true&sidebarMode=learn" target="_blank">this link</a>. to sign up and start simulating!', |
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examples= path, |
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) |
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iface.launch() |
