from flask import Flask, request, jsonify ,render_template , redirect from pydantic import BaseModel import pickle import json import pandas as pd from tensorflow.keras.models import load_model from tensorflow.keras.preprocessing import image from tensorflow.keras.applications.inception_v3 import preprocess_input import numpy as np import os import gdown import lightgbm as lgb from PIL import Image from flask_cors import CORS, cross_origin app = Flask(__name__) id = "1dPrnyH7y9ojSHaOOOTkbGkCnhwYvMxab" output = "disease_new.h5" gdown.download(id=id, output=output, quiet=False) CORS(app) app.config['CORS_HEADERS'] = 'Content-Type' crop_disease_ml=load_model('disease_new.h5') @app.route("/upload-image", methods=["POST"]) @cross_origin() def upload_image(): # if request.method == "POST": if request.files: imag = request.files["image"] try: contents = imag.read() with open(imag.filename, 'wb') as f: f.write(contents) except Exception: return {"message": "There was an error uploading the file"} finally: imag.close() print(imag) classes = ['Pepper bell Bacterial spot', 'Pepper bell healthy', 'Potato Early blight', 'Potato Late blight', 'Potato healthy', 'Tomato Bacterial spot', 'Tomato Early blight', 'Tomato Late blight', 'Tomato Leaf Mold', 'Tomato Septoria leaf spot', 'Tomato Spider mites Two spotted spider mite', 'Tomato Target Spot', 'Tomato Tomato YellowLeaf Curl Virus', 'Tomato Tomato mosaic virus', 'Tomato healthy'] img=image.load_img(str(imag.filename),target_size=(224,224)) x=image.img_to_array(img) x=x/255 img_data=np.expand_dims(x,axis=0) prediction = crop_disease_ml.predict(img_data) predictions = list(prediction[0]) max_num = max(predictions) index = predictions.index(max_num) print(classes[index]) os.remove(str(imag.filename)) response = jsonify(output=classes[index]) # response.headers.add('Access-Control-Allow-Origin', '*') # response.headers.add('Access-Control-Allow-Headers', 'Content-Type,Authorization') # response.headers.add('Access-Control-Allow-Methods', 'GET,PUT,POST,DELETE,OPTIONS') return response if __name__ =="__main__": app.run(debug=False,host="0.0.0.0",port=5000)