fix issues

.gitignore

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+dataset/
+NN.py
+test.py
+.venv

README.md

@@ -1,8 +1,8 @@
 ---
 title: FLL Innovation
-emoji: 📈
-colorFrom: blue
-colorTo: pink
+emoji: 😻
+colorFrom: red
+colorTo: green
 sdk: gradio
 sdk_version: 6.3.0
 app_file: app.py

app.py

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+import os
+import gradio as gr
+import numpy as np
+from PIL import Image
+import tensorflow as tf
+
+print("Building model architecture...")
+base_model = tf.keras.applications.MobileNetV2(
+    input_shape=(224, 224, 3),
+    include_top=False,
+    weights="imagenet"
+)
+base_model.trainable = False
+
+model = tf.keras.models.Sequential([
+    base_model,
+    tf.keras.layers.GlobalAveragePooling2D(),
+    tf.keras.layers.Dense(128, activation="relu"),
+    tf.keras.layers.Dropout(0.3),
+    tf.keras.layers.Dense(2, activation="softmax")
+])
+
+print("Loading weights...")
+model.load_weights("model.weights.h5")
+print("Model ready!")
+
+LABELS = ["preserved", "looted"]
+IMG_SIZE = (224, 224)
+
+def preprocess(img: Image.Image):
+    img = img.convert("RGB").resize(IMG_SIZE)
+    arr = np.array(img) / 255.0
+    arr = np.expand_dims(arr, 0).astype(np.float32)
+    return arr
+
+def predict(image: Image.Image):
+    x = preprocess(image)
+    probs = model.predict(x)[0]
+    
+    result = {LABELS[0]: float(probs[0]), LABELS[1]: float(probs[1])}
+    idx = int(np.argmax(probs))
+    summary = f"Prediction: **{LABELS[idx]}** ({float(probs[idx]):.1%} confidence)"
+    
+    return result, summary
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil", label="Upload photo"),
+    outputs=[gr.Label(num_top_classes=2, label="Prediction"), gr.Textbox(label="Summary")],
+    title="Preserved vs Looted Classifier",
+    description="Upload a photo to classify as preserved or looted."
+)
+
+if __name__ == "__main__":
+    iface.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)))

model.weights.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:adbf23137123a4490a24b8f8a78e6035fbccb0f4348b07127c191d58824e2703
+size 11437088

requirements.txt

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+gradio
+tensorflow
+pillow
+numpy
+huggingface-hub
+