import plantvision import requests from io import BytesIO import pickle as pkl from flask import Flask, render_template, request, session, jsonify, url_for from PIL import Image import os import time import random from pathlib import Path THIS_FOLDER = Path(__file__).parent.resolve() app = Flask(__name__) app.secret_key = 'pi-33pp-co-sk-33' app.template_folder = os.path.abspath(f'{THIS_FOLDER}/web/templates') app.static_folder = os.path.abspath(f'{THIS_FOLDER}/web/static') print(app.static_folder) flowerLayers = None leafLayers = None fruitLayers = None @app.route('/') def home(): return render_template('index.html') @app.route('/guess', methods=['POST']) def guess(): global flowerLayers, leafLayers, fruitLayers if request.method == 'POST': print('Thinking...') img = request.files.get('uploaded-image') feature = request.form.get('feature') tensor = plantvision.processImage(img, feature) predictions = plantvision.see(tensor, feature, 6) with open(f'{THIS_FOLDER}/resources/speciesNameToKey.pkl','rb') as f: speciesNameToKey = pkl.load(f) with open(f'{THIS_FOLDER}/resources/speciesNameToVernacular.pkl','rb') as f: speciesNameToVernacular = pkl.load(f) with open(f'{THIS_FOLDER}/resources/{feature}speciesIndexDict.pkl','rb') as f: speciesNameToIndex = pkl.load(f) urls = [] predicted_image_urls = [] for p in predictions: key = speciesNameToKey[p] img = speciesNameToIndex[p] query = '' for i in p.split(' '): query += i query += '+' urls.append(f'https://www.google.com/search?q={query[:-1]}') predicted_image_urls.append(f"https://storage.googleapis.com/bmllc-images-bucket/images/img{img}.jpeg") names = [] for p in predictions: try: names.append(speciesNameToVernacular[p]) except: names.append(p) response = { 'names': names, 'species': predictions, 'predictions': urls, 'images': predicted_image_urls } return jsonify(response) if __name__ == '__main__': app.run(port=7860,host='0.0.0.0',debug=True)