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import torch |
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import gradio as gr |
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from huggingface_hub import hf_hub_download |
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from PIL import Image |
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REPO_ID = "thoucentric/Shelf_Objects_Detection_Yolov7_Pytorch" |
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FILENAME = "best.pt" |
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yolov7_custom_weights = hf_hub_download(repo_id=REPO_ID, filename=FILENAME) |
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model = torch.hub.load('Owaiskhan9654/yolov7-1:main',model='custom', path_or_model=yolov7_custom_weights, force_reload=True) |
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def object_detection(image: gr.inputs.Image = None): |
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results = model(image) |
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results.render() |
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count_dict = results.pandas().xyxy[0]['name'].value_counts().to_dict() |
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if len(count_dict)>0: |
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return Image.fromarray(results.imgs[0]),str(count_dict) |
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else: |
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return Image.fromarray(results.imgs[0]),'No object Found. Add more Custom classes in the training set' |
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title = "<center><a href=\"https://thoucentric.com/\"><img src='https://thoucentric.com/wp-content/themes/cevian-child/assets/img/Thoucentric-Logo.png' alt='Thoucentric-Logo'></a></center><br>Yolov7 Custom" |
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inputs = gr.inputs.Image(shape=(640, 640), image_mode="RGB", source="upload", label="Upload Image", optional=False) |
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outputs = gr.outputs.Image(type="pil", label="Output Image") |
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outputs_cls = gr.Label(label= "Categories Detected Proportion Statistics" ) |
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Custom_description="<center>Custom Training Performed on Kaggle <a href='https://www.kaggle.com/code/owaiskhan9654/shelf-object-detection-yolov7-pytorch/notebook' style='text-decoration: underline' target='_blank'>Link</a> </center><br> <center>Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors </center> <br> Works on around <b>140</b> general items in Stores" |
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Footer = ( |
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"<br><br><br><br><center><b>Item Classes it will detect(Total 140 Classes) <br></b> " |
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"<textarea name='w3review' rows='6' cols='120'>" |
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"'Drawbar box', 'Disposable cups', 'Makeup tools', 'Television', 'Toothpaste', 'Herbal tea', 'Skate', 'Coat hanger', 'Soy sauce', " |
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"'Tea beverage', 'Sour Plum Soup', 'Pie', 'Chopping block', 'Refrigerator', 'Trousers', 'Oats', 'Rubber ball', 'Soap', 'Pasta', 'Juicer', " |
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"'Walnut powder', 'Toothbrush', 'Chopsticks', 'Mouth wash', 'Adult socks', 'Dinner plate', 'Baby milk powder', 'Soymilk', 'Cutter', 'Hair drier', " |
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"'Electric frying pan', 'Children hats', 'Cake', 'Trash', 'Children underwear', 'Guozhen', 'Disposable bag', 'Jacket', 'Baby carriage', 'Bowl', " |
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"'Baby tableware', 'Emulsion', 'Red wine', 'Mixed congee', 'Spoon', 'Dried meat', 'Dairy', 'Chewing gum', 'Cooking wine', 'Electromagnetic furnace', " |
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"'Facial Cleanser', 'Sports cup', 'Quick-frozen Wonton', 'Dried fish', 'Rice cooker', 'Children shoes', 'Band aid', 'Biscuits', 'Soybean Milk machine', " |
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"'Pen', 'Baby crib', 'Hair gel', 'Children Toys', 'Ice cream', 'Washing machine', 'Hot strips', 'Air conditioning fan', 'Pencil case', 'Hair conditioner'," |
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"'Razor', 'Children Socks', 'Basin', 'Chocolates', 'Shampoo', 'Soup ladle', 'Men underwear', 'Baby washing and nursing supplies', 'Noodle', 'Tampon', " |
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"'Forks', 'Liquor and Spirits', 'Bath lotion', 'Knives', 'Quick-frozen dumplings', 'Socket', 'Notebook', 'Bedding set', 'Storage box', 'Ginger Tea', " |
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"'Basketball', 'Baby Toys', 'Storage bottle', 'Instant noodles', 'Baby Furniture', 'Thermos bottle', 'Hair dye', 'Fish tofu', 'Vinegar', 'Comb', " |
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"'Carbonated drinks', 'Sauce', 'Adult shoes', 'Quick-frozen Tangyuan', 'Stool', 'Football', 'Baby diapers', 'Lotus root flour', 'Air conditioner', " |
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"'Badminton', 'Knapsack', 'Adult Diapers', 'Flour', 'Sesame paste', 'Pot shovel', 'Electric kettle', 'Mug', 'Electric iron', 'Lingerie', 'Tea', " |
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"'Food box', 'Electric Hot pot', 'Baby slippers', 'Potato chips', 'Electric steaming pan', 'Rise', 'Adult hat', 'Can', 'Care Kit', 'Cotton swab', " |
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"'Baby handkerchiefs ', 'Fresh-keeping film', 'Dried beans', 'Electric fan', 'Desk lamp', 'Cocktail', 'Skincare set', 'Adult milk powder', " |
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"'Microwave Oven', 'Coffee', 'Facial mask'.</textarea></center>" |
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"<br><br><br><br><center>Model Trained by: Owais Ahmad Data Scientist at <b><a href=\"https://thoucentric.com/\">Thoucentric</a></b><br></center>" |
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"<center> Model Trained Kaggle Kernel <a href=\"https://www.kaggle.com/code/owaiskhan9654/shelf-object-detection-yolov7-pytorch/notebook\">Link</a> <br></center>" |
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"<center> HuggingFace🤗 Model Deployed Repository <a href=\"https://huggingface.co/thoucentric/Shelf_Objects_Detection_Yolov7_Pytorch\">Link</a> <br></center>" |
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"<center> Copyright © 2023 Thoucentric.All Rights Reserved</center>" |
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) |
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examples1=[["Images/Image1.jpg"],["Images/Image2.jpg"],["Images/Image3.jpg"],["Images/Image4.jpg"],["Images/Image5.jpg"],["Images/Image6.jpg"],["Images/Image7.jpg"],["Images/Image8.jpg"],["Images/Image9.jpg"],["Images/Image10.jpg"],["Images/Image11.jpg"],["Images/Image12.jpg"],["Images/Image13.jpg"],["Images/Image14.jpg"],["Images/Image15.jpg"],["Images/Image16.jpg"],["Images/Image17.jpg"],["Images/Image18.jpg"],["Images/Image19.jpg"],["Images/Image20.jpg"]] |
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Top_Title="<center><a href=\"https://thoucentric.com/\"><img src='https://thoucentric.com/wp-content/themes/cevian-child/assets/img/Thoucentric-Logo.png' alt='Thoucentric-Logo'></a></center><br>Yolov7 🚀 Custom Trained on around 140 general items in Stores" |
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css = ".output-image {height: 50rem important; width: 100% !important;}, .input-image {height: 50rem !important; width: 100% !important;}" |
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css = ".image-preview {height: auto important;}" |
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gr.Interface( |
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fn=object_detection, |
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inputs=inputs, |
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outputs=[outputs,outputs_cls], |
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title=Top_Title, |
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description=Custom_description, |
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article=Footer, |
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cache_examples= False, |
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allow_flagging='never', |
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examples=examples1).launch(debug=True) |
