Upload 4 files

Dockerfile

@@ -0,0 +1,18 @@
+# Use Python 3.9
+FROM python:3.9
+
+# Set working directory
+WORKDIR /code
+
+# Copy requirements and install them
+COPY ./requirements.txt /code/requirements.txt
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# Copy all files
+COPY . .
+
+# Grant permissions
+RUN chmod 777 .
+
+# Start the server
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -0,0 +1,44 @@
+from fastapi import FastAPI, File, UploadFile
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+import io
+
+app = FastAPI()
+
+# Load the model once when server starts
+model = tf.keras.models.load_model("orange_disease_model.h5")
+
+# Define your classes (Make sure these match your labels.txt!)
+CLASS_NAMES = [
+    'Citrus canker', 'Citrus greening', 'Citrus mealybugs', 'Die back', 
+    'Foliage damaged', 'Healthy leaf', 'Powdery mildew', 'Shot hole', 
+    'Spiny whitefly', 'Yellow dragon', 'Yellow leaves'
+]
+
+@app.get("/")
+def home():
+    return {"message": "Orange Disease Detection API is Running!"}
+
+@app.post("/predict")
+async def predict(file: UploadFile = File(...)):
+    # 1. Read the image uploaded by the user
+    image_data = await file.read()
+    image = Image.open(io.BytesIO(image_data))
+    
+    # 2. Preprocess (Resize to 224x224 and Normalize)
+    image = image.resize((224, 224))
+    img_array = tf.keras.preprocessing.image.img_to_array(image)
+    img_array = tf.expand_dims(img_array, 0) # Create a batch
+    img_array = img_array / 255.0
+
+    # 3. Predict
+    predictions = model.predict(img_array)
+    predicted_class = CLASS_NAMES[np.argmax(predictions[0])]
+    confidence = float(np.max(predictions[0]))
+
+    # 4. Return JSON
+    return {
+        "class": predicted_class,
+        "confidence": confidence
+    }

orange_disease_model.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5433c9686e86c839486833e73c98fbf57c4ebb36c9c79a492dd2ddec33b4fc7c
+size 11557472

requirements.txt

@@ -0,0 +1,6 @@
+fastapi
+uvicorn
+tensorflow-cpu
+pillow
+python-multipart
+numpy