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from tensorflow.keras.models import load_model |
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from tensorflow.keras.applications.efficientnet_v2 import preprocess_input |
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import numpy as np |
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import gradio as gr |
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model = load_model("best_model_finetuned224.keras") |
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class_names = ['Cardboard', 'Glass', 'Metal', 'Paper', 'Plastic', 'Trash'] |
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def classify_image(img): |
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try: |
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if img is None: |
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return "<div style='color:red;'>No image received. Please upload or capture an image.</div>" |
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img = img.resize((224, 224)) |
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img_array = np.array(img, dtype=np.float32) |
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if img_array.shape != (224, 224, 3): |
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return f"<div style='color:red;'>Unexpected input shape: {img_array.shape}</div>" |
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img_array = preprocess_input(img_array) |
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img_array = np.expand_dims(img_array, axis=0) |
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prediction = model.predict(img_array)[0] |
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predicted_class_index = np.argmax(prediction) |
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predicted_class_name = class_names[predicted_class_index] |
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confidence = float(prediction[predicted_class_index]) |
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return f""" |
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<div style='text-align: center; font-size: 28px; font-weight: bold; color: #00FFAA; font-family: Arial, sans-serif;'> |
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Prediction: {predicted_class_name}<br> |
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<span style='font-size: 20px; color: #888;'>Confidence: {confidence:.2%}</span> |
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</div> |
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""" |
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except Exception as e: |
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return f"<div style='color:red;'>Error during prediction: {str(e)}</div>" |
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iface = gr.Interface( |
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fn=classify_image, |
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inputs=gr.Image(type="pil", sources=["upload", "webcam"],), |
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outputs=gr.HTML(), |
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title="♻️ Waste Material Classifier", |
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description="Upload or capture an image and this AI model will classify it into one of six recyclable waste categories.", |
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article=""" |
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<br><br> |
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<div style='display: flex; justify-content: center; gap: 60px; color: #b0b0b0; font-size: 14px; flex-wrap: wrap;'> |
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<div>Powered by EfficientNetV2</div> |
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<div>Built with TensorFlow and Gradio</div> |
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</div> |
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<div style='text-align: center; color: #b0b0b0; font-size: 14px; margin-top: 10px; font-family: monospace'> |
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Developed by Saaiem Salaar |
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<br> |
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<a href='https://github.com/Salaar-Saaiem' target='_blank' style='margin: 0 8px; display: inline-block;'> |
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<img src='https://cdn-icons-png.flaticon.com/512/25/25231.png' width='20' height='20' alt='GitHub' style='vertical-align: middle;' /> |
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</a> |
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<a href='https://www.linkedin.com/in/salaarsaaiem525/' target='_blank' style='margin: 0 8px; display: inline-block;'> |
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<img src='https://cdn-icons-png.flaticon.com/512/174/174857.png' width='20' height='20' alt='LinkedIn' style='vertical-align: middle;' /> |
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</a> |
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</div> |
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""" |
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) |
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iface.launch(share=True) |
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