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  1. Inception_V3.h5 +3 -0
  2. app.py +38 -0
  3. requirements.txt +10 -0
Inception_V3.h5 ADDED
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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
app.py ADDED
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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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+
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+ # ตั้งค่า logging
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+ logging.basicConfig(filename="gradio_usage.log", level=logging.INFO)
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+
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+ # โหลดโมเดล InceptionV3
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+ model = tf.keras.models.load_model("Inception_V3.h5")
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+
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+ class_names = ["Benign", "Malignant"]
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+
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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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+
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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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+
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+ logging.info(f"Prediction result: {confidence_dict}")
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+ return confidence_dict
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+
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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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+
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+ interface.launch()
requirements.txt ADDED
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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