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Merge branch 'main' of https://huggingface.co/spaces/Dinoking/Gc-v6
Browse files
app.py
CHANGED
@@ -7,16 +7,16 @@ import keras.applications.xception as xception
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from tensorflow.keras.models import load_model
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# load model
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model = load_model('
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classnames = ['battery','
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def predict_image(img):
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img_4d=img.reshape(-1,320, 320,3)
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prediction=model.predict(img_4d)[0]
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return {classnames[i]: float(prediction[i]) for i in range(
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image = gr.inputs.Image(shape=(320, 320))
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label = gr.outputs.Label(num_top_classes=3)
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@@ -25,4 +25,4 @@ examples = ['battery.jpg','cardboard.jpeg','clothes.jpeg','glass.jpg','metal.jpg
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article="<p style='text-align: center'>Made by Aditya Narendra with 🖤</p>"
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gr.Interface(fn=predict_image, inputs=image, title="Garbage Classifier",
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description="This is a Garbage Classification Model Trained using Xception Net.Deployed to Hugging Faces using Gradio.",outputs=label,article=article,enable_queue=enable_queue,examples=examples,interpretation='default').launch(share="True")
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from tensorflow.keras.models import load_model
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# load model
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model = load_model('model804.h5')
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classnames = ['battery','cardboard','clothes','food','glass','medical','metal','paper','plastic','shoes']
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def predict_image(img):
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img_4d=img.reshape(-1,320, 320,3)
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prediction=model.predict(img_4d)[0]
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return {classnames[i]: float(prediction[i]) for i in range(10)}
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image = gr.inputs.Image(shape=(320, 320))
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label = gr.outputs.Label(num_top_classes=3)
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article="<p style='text-align: center'>Made by Aditya Narendra with 🖤</p>"
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gr.Interface(fn=predict_image, inputs=image, title="Garbage Classifier",
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description="This is a Garbage Classification Model Trained using Xception Net on DS11 Mod(Seg10 V4).Deployed to Hugging Faces using Gradio.",outputs=label,article=article,enable_queue=enable_queue,examples=examples,interpretation='default').launch(share="True")
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