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import gradio as gr |
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from transformers import pipeline |
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examples = ["examples/example_0.jpg", |
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"examples/example_1.png", |
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"examples/example_2.png", |
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"examples/example_3.png", |
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"examples/example_4.jpg", |
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"examples/example_5.png"] |
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pipe = pipeline(task="image-classification", |
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model="Kaludi/csgo-weapon-classification") |
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gr.Interface.from_pipeline(pipe, |
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title="CSGO Weapon Image Classification", |
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description = "This is a CSGO Weapon Classifier Model that has been trained by <strong><a href='https://huggingface.co/Kaludi'>Kaludi</a></strong> to recognize <strong>11</strong> different types of Counter-Strike: Global Offensive (CSGO) Weapons, which include <strong>AK-47,AWP,Famas,Galil-AR,Glock,M4A1,M4A4,P-90,SG-553,UMP,USP</strong>. The model is capable of accurately classifying the weapon name present in an image. With its deep understanding of the characteristics of each weapon in the game, the model is a valuable tool for players and fans of CSGO.", |
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article = "<p style='text-align: center'><a href='https://github.com/Kaludii'>Github</a> | <a href='https://huggingface.co/Kaludi'>HuggingFace</a></p>", |
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examples=examples, |
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).launch() |