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Runtime error
| import tensorflow as tf | |
| import numpy as np | |
| import json | |
| from fastapi import FastAPI, File, UploadFile | |
| from PIL import Image | |
| import io | |
| # ✅ Load .keras model directly | |
| model = tf.keras.models.load_model( | |
| "leaf_disease_efficientnetB0_fixed.keras" | |
| ) | |
| # Load class names | |
| with open("class_names.json") as f: | |
| class_names = json.load(f) | |
| IMG_SIZE = 224 | |
| app = FastAPI() | |
| def preprocess_image(image): | |
| image = image.resize((IMG_SIZE, IMG_SIZE)) | |
| image = np.array(image).astype(np.float32) | |
| image = tf.keras.applications.efficientnet.preprocess_input(image) | |
| image = np.expand_dims(image, axis=0) | |
| return image | |
| def home(): | |
| return {"message": "Leaf Disease Model API is running"} | |
| async def predict(file: UploadFile = File(...)): | |
| contents = await file.read() | |
| image = Image.open(io.BytesIO(contents)).convert("RGB") | |
| image = preprocess_image(image) | |
| predictions = model.predict(image) | |
| predicted_index = int(np.argmax(predictions)) | |
| confidence = float(np.max(predictions)) | |
| predicted_class = class_names[predicted_index] | |
| return { | |
| "class": predicted_class, | |
| "confidence": confidence | |
| } |