import os import requests from requests.auth import HTTPBasicAuth from PIL import Image from io import BytesIO from urllib.parse import urlparse import os from inference_sdk import InferenceHTTPClient import base64 UPLOAD_FOLDER = '/code/uploads' if not os.path.exists(UPLOAD_FOLDER): os.makedirs(UPLOAD_FOLDER) def predict_pest(filepath): CLIENT = InferenceHTTPClient( api_url="https://detect.roboflow.com", api_key="oF1aC4b1FBCDtK8CoKx7" ) result = CLIENT.infer(filepath, model_id="pest-detection-ueoco/1") return result['predicted_classes'][0] def predict_disease(filepath): CLIENT = InferenceHTTPClient( api_url="https://classify.roboflow.com", api_key="oF1aC4b1FBCDtK8CoKx7" ) result = CLIENT.infer(filepath, model_id="plant-disease-detection-iefbi/1") return result['predicted_classes'][0] def convert_img(url, account_sid, auth_token): try: # Make the request to the media URL with authentication response = requests.get(url, auth=HTTPBasicAuth(account_sid, auth_token)) response.raise_for_status() # Raise an error for bad responses # Determine a filename from the URL parsed_url = urlparse(url) media_id = parsed_url.path.split('/')[-1] # Get the last part of the URL path filename = f"downloaded_media_{media_id}" # Save the media content to a file media_filepath = os.path.join(UPLOAD_FOLDER, filename) with open(media_filepath, 'wb') as file: file.write(response.content) print(f"Media downloaded successfully and saved as {media_filepath}") # Convert the saved media file to an image with open(media_filepath, 'rb') as img_file: image = Image.open(img_file) # Optionally, convert the image to JPG and save in UPLOAD_FOLDER converted_filename = f"image.jpg" converted_filepath = os.path.join(UPLOAD_FOLDER, converted_filename) image.convert('RGB').save(converted_filepath, 'JPEG') return converted_filepath except requests.exceptions.HTTPError as err: print(f"HTTP error occurred: {err}") except Exception as err: print(f"An error occurred: {err}")