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Runtime error
| import gradio as gr | |
| import pandas as pd | |
| import numpy as np | |
| import os | |
| from PIL import Image | |
| import requests | |
| from io import BytesIO | |
| from imageai.Prediction import ImagePrediction | |
| import csv | |
| # Load the protected-birds.csv file | |
| protected_birds = pd.read_csv('protected-birds.csv') | |
| protected_birds = protected_birds.dropna() | |
| protected_birds = protected_birds['Common Name'].str.lower().values | |
| # Load the image ai model | |
| model = ImagePrediction() | |
| model.setModelTypeAsResNet() | |
| model.setModelPath("resnet50_weights_tf_dim_ordering_tf_kernels.h5") | |
| model.loadModel() | |
| # Function to check if the feather is from a protected bird | |
| def check_feather(image): | |
| # Load the image | |
| response = requests.get(image) | |
| img = Image.open(BytesIO(response.content)) | |
| img.save('image.jpg') | |
| # Make a prediction | |
| model_predictions, probabilities = model.predictImage('image.jpg', result_count=5) | |
| # Check if the feather is from a protected bird | |
| protected = False | |
| protected_birds_list = [] | |
| for bird in protected_birds: | |
| for prediction in model_predictions: | |
| if bird in prediction.lower(): | |
| protected = True | |
| protected_birds_list.append([bird, prediction, probabilities[model_predictions.index(prediction)]]) | |
| if protected: | |
| # Display the results | |
| gr.Interface(fn=lambda: protected_birds_list, inputs="text", outputs="text").launch() | |
| user_verification = gr.inputs.Checkbox(label="Verify the results") | |
| if user_verification: | |
| # Output the result in a table format | |
| gr.Interface(fn=lambda: protected_birds_list, inputs=user_verification, outputs="html").launch() | |
| # Prompt user to make a report | |
| gr.Interface(fn=lambda: "If confident, report to: https://www.fws.gov/contact-us", inputs=user_verification, outputs="text").launch() | |
| else: | |
| gr.Interface(fn=lambda: "No protected bird detected", inputs=image, outputs="text").launch() | |
| return protected, protected_birds_list | |
| # Gradio interface | |
| image = gr.inputs.Image() | |
| gr.Interface(fn=check_feather, inputs=image, outputs="text").launch() |