devdatanalytics/react

1from flask import Flask, request, jsonify2from fastai.vision.all import *3from huggingface_hub import from_pretrained_fastai4from PIL import Image5import io6 7app = Flask(__name__)8 9def classify_image(image_file):10    # Load the trained model from Huggingface11    learn = from_pretrained_fastai("devdatanalytics/commonbean")12    13    # Open the image file14    img = Image.open(image_file)15    16    # Perform any necessary preprocessing on the image17    # For example, resizing or normalization18    img = img.resize((224, 224))  # Resize the image to match the model's input size19    20    # Convert the image to a BytesIO object21    img_bytes = io.BytesIO()22    img.save(img_bytes, format='PNG')23    img_bytes.seek(0)24    25    # Perform the classification26    pred_class, pred_idx, probs = learn.predict(img_bytes)27    28    # Return the classification results29    return f"Predicted Class: {pred_class}, Probability: {probs[pred_idx]:.2f}"30 31@app.route('/classify', methods=['POST'])32def classify():33    if 'image' not in request.files:34        return "No image file found", 40035    36    image_file = request.files['image']37    38    # Perform image classification39    classification_results = classify_image(image_file)40    41    return jsonify(classification_results)42 43if __name__ == '__main__':44    app.run()