Initial commit Plantopia

README.md

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----
-title: Plantopia
-emoji: 🦀
-colorFrom: indigo
-colorTo: green
-sdk: gradio
-sdk_version: 5.31.0
-app_file: app.py
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import tensorflow as tf
+import numpy as np
+import pickle
+from PIL import Image
+
+# Load model & label encoder sekali di awal
+model = tf.keras.models.load_model("my_cnn_model.h5")
+with open("label_encoder.pkl", "rb") as f:
+    label_encoder = pickle.load(f)
+
+# Daftar label
+class_names = label_encoder.inverse_transform(np.arange(len(label_encoder.classes_)))
+
+def predict(img: Image.Image):
+    img = img.resize((224, 224))
+    img_array = np.array(img) / 255.0
+    img_array = np.expand_dims(img_array, axis=0)
+
+    prediction = model.predict(img_array)[0]
+    predicted_index = np.argmax(prediction)
+    predicted_label = class_names[predicted_index]
+    predicted_confidence = prediction[predicted_index] * 100
+
+    result = f"✅ Prediksi penyakit tanaman: {predicted_label}\n"
+    result += f"🎯 Akurasi keyakinan model (confidence): {predicted_confidence:.2f}%\n\n"
+    result += "--- Detail Probabilitas untuk Semua Kelas ---\n"
+    for label, prob in zip(class_names, prediction):
+        result += f"{label:15}: {prob:.4f}\n"
+
+    return result
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="Deteksi Penyakit Daun 🌿",
+    description="Upload gambar daun dan sistem akan memprediksi penyakitnya berdasarkan model CNN yang telah dilatih.",
+    allow_flagging="never"
+).launch()

label_encoder.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8ea2192a47d152a2d6d2a160d64d15c33cada8ce580d22e3ae3deb78ffcdedfd
+size 767

plantopia.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5fe734ac4a78796b2cbfff2f89ccc032b71e4d1739763388f725d475749b4d47
+size 80486016

requirements.txt

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+tensorflow>=2.11.0
+pandas
+numpy
+matplotlib
+seaborn
+Pillow
+scikit-image
+opencv-python-headless
+scikit-learn
+opendatasets