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Browse files- Inception_V3.h5 +3 -0
- app.py +38 -0
- requirements.txt +10 -0
Inception_V3.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:6470641316e4c8bdd606e155460d443db7330cae05626623183145fd3f28f319
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size 98695104
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app.py
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import logging
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import gradio as gr
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import tensorflow as tf
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from tensorflow.keras.applications.inception_v3 import preprocess_input
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from tensorflow.keras.preprocessing import image
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import numpy as np
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# ตั้งค่า logging
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logging.basicConfig(filename="gradio_usage.log", level=logging.INFO)
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# โหลดโมเดล InceptionV3
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model = tf.keras.models.load_model("Inception_V3.h5")
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class_names = ["Benign", "Malignant"]
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def predict(img):
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logging.info("Predict function called.")
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img = img.resize((224, 224))
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img_array = image.img_to_array(img)
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img_array = np.expand_dims(img_array, axis=0)
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img_array = preprocess_input(img_array)
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predictions = model.predict(img_array)
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predictions = predictions[0]
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confidence_dict = {class_names[i]: float(predictions[i]) for i in range(len(class_names))}
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logging.info(f"Prediction result: {confidence_dict}")
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return confidence_dict
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interface = gr.Interface(
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fn=predict,
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inputs=gr.Image(type="pil", label="Upload an Image"),
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outputs=gr.Label(num_top_classes=2, label="Predicted Class"),
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title="Melanoma Classification with InceptionV2",
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description="Upload an image to classify it into one of the classes."
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)
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interface.launch()
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requirements.txt
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tensorflow==2.17.0
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numpy>=1.23.5, <2.0.0
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Pillow==9.2.0
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gradio==3.0.7
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httpx==0.21.1
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seaborn==0.11.2
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matplotlib==3.5.1
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scikit-learn==1.1.3
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Cython==0.29.32
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ml-dtypes<0.5.0,>=0.3.1
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