Upload model cnn

app.py

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+from fastapi import FastAPI, File, UploadFile
+from fastapi.responses import JSONResponse
+from fastapi.middleware.cors import CORSMiddleware
+import numpy as np
+import tensorflow as tf
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing import image
+from PIL import Image
+from io import BytesIO
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # sesuaikan jika perlu
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+MODEL_PATH = 'model_cnn.h5'
+IMG_HEIGHT = 224
+IMG_WIDTH = 224
+
+class_names = [
+    'freshapples', 'freshbanana', 'freshbittergroud', 'freshcapsicum', 'freshcucumber',
+    'freshokra', 'freshoranges', 'freshpotato', 'freshtomato',
+    'rottenapples', 'rottenbanana', 'rottenbittergroud', 'rottencapsicum', 'rottencucumber',
+    'rottenokra', 'rottenoranges', 'rottenpotato', 'rottentomato'
+]
+
+model = load_model(MODEL_PATH)
+
+def read_imagefile(file) -> Image.Image:
+    image = Image.open(BytesIO(file)).convert("RGB")
+    return image
+
+def predict(img: Image.Image):
+    img = img.resize((IMG_WIDTH, IMG_HEIGHT))
+    img_array = image.img_to_array(img)
+    img_array = np.expand_dims(img_array, axis=0)
+
+    prediction = model.predict(img_array)
+    predicted_class = np.argmax(prediction[0])
+    confidence = float(prediction[0][predicted_class]) * 100
+
+    return class_names[predicted_class], confidence
+
+@app.post("/predict")
+async def predict_image(file: UploadFile = File(...)):
+    try:
+        img = read_imagefile(await file.read())
+        pred_class, confidence = predict(img)
+        response = {
+            "filename": file.filename,
+            "title": "Prediction Result",
+            "message": f"The item is classified as: {pred_class}",
+            "confidence": f"{confidence:.2f}",
+            "details": [f"Class: {pred_class}", f"Confidence: {confidence:.2f}%"]
+        }
+        return JSONResponse(content=response)
+    except Exception as e:
+        return JSONResponse(content={"error": str(e)}, status_code=500)
+
+# Komentar atau hapus bagian run uvicorn karena Spaces otomatis menjalankan app
+# if __name__ == "__main__":
+#     import uvicorn
+#     uvicorn.run("app:app", host="0.0.0.0", port=8000, reload=True)

model_cnn.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6b9ec1e00e08442f5f94e95379b8040afe19c7ea218e00fab0096e7a679d09fb
+size 5539336

requirements.txt

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+absl-py==2.3.0
+annotated-types==0.7.0
+anyio==4.9.0
+appnope==0.1.4
+asttokens==3.0.0
+astunparse==1.6.3
+certifi==2025.4.26
+charset-normalizer==3.4.2
+chex==0.1.89
+click==8.2.1
+comm==0.2.2
+debugpy==1.8.14
+decorator==5.2.1
+etils==1.12.2
+executing==2.2.0
+fastapi==0.115.12
+flatbuffers==25.2.10
+flax==0.10.4
+fsspec==2025.5.1
+gast==0.6.0
+google-pasta==0.2.0
+grpcio==1.72.1
+h11==0.16.0
+h5py==3.13.0
+humanize==4.12.3
+idna==3.10
+importlib_resources==6.5.2
+ipykernel==6.29.5
+ipython==9.3.0
+ipython_pygments_lexers==1.1.1
+jax==0.4.34
+jaxlib==0.4.34
+jedi==0.19.2
+jupyter_client==8.6.3
+jupyter_core==5.8.1
+keras==3.10.0
+libclang==18.1.1
+Markdown==3.8
+markdown-it-py==3.0.0
+MarkupSafe==3.0.2
+matplotlib-inline==0.1.7
+mdurl==0.1.2
+ml-dtypes==0.3.2
+msgpack==1.1.0
+namex==0.1.0
+nest-asyncio==1.6.0
+numpy==1.26.4
+opt_einsum==3.4.0
+optax==0.2.4
+optree==0.16.0
+orbax-checkpoint==0.11.5
+packaging==23.2
+pandas==2.3.0
+parso==0.8.4
+pexpect==4.9.0
+pillow==11.2.1
+platformdirs==4.3.8
+prompt_toolkit==3.0.51
+protobuf==4.25.8
+psutil==7.0.0
+ptyprocess==0.7.0
+pure_eval==0.2.3
+pydantic==2.11.5
+pydantic_core==2.33.2
+Pygments==2.19.1
+python-dateutil==2.9.0.post0
+python-multipart==0.0.20
+pytz==2025.2
+PyYAML==6.0.2
+pyzmq==26.4.0
+requests==2.32.3
+rich==14.0.0
+scipy==1.15.3
+simplejson==3.20.1
+six==1.17.0
+sniffio==1.3.1
+stack-data==0.6.3
+starlette==0.46.2
+tensorboard==2.16.2
+tensorboard-data-server==0.7.2
+tensorflow==2.16.1
+tensorflow-hub==0.16.1
+tensorflow-io-gcs-filesystem==0.37.1
+tensorflow_decision_forests==1.9.0
+tensorflowjs==4.22.0
+tensorstore==0.1.74
+termcolor==3.1.0
+tf_keras==2.16.0
+toolz==1.0.0
+tornado==6.5.1
+traitlets==5.14.3
+treescope==0.1.9
+typing-inspection==0.4.1
+typing_extensions==4.14.0
+tzdata==2025.2
+urllib3==2.4.0
+uvicorn==0.34.3
+wcwidth==0.2.13
+Werkzeug==3.1.3
+wrapt==1.17.2
+wurlitzer==3.1.1
+zipp==3.22.0