| import gradio as gr | |
| import tensorflow as tf | |
| title = "Covid 19 Prediction App using X-ray Images" | |
| head = ( | |
| "<center>" | |
| "Upload an X-ray image to check for covid19. The app is for research purposes and not clinically authorized" | |
| "</center>" | |
| ) | |
| title = "Covid 19 Prediction App using X-ray Images" | |
| head = ( | |
| "<center>" | |
| "Upload an X-ray image to check for covid19. The app is for research purposes and not clinically authorized" | |
| "</center>" | |
| ) | |
| def predict_input_image(img): | |
| from transformers import AutoFeatureExtractor, AutoModelForImageClassification | |
| extractor = AutoFeatureExtractor.from_pretrained("swww/test") | |
| model = AutoModelForImageClassification.from_pretrained("swww/test") | |
| image = gr.inputs.Image(shape=(500, 500), image_mode='L', invert_colors=False, source="upload") | |
| label = gr.outputs.Label() | |
| iface = gr.Interface(fn=predict_input_image, inputs=image, outputs=label,title=title, description=head) | |
| iface.launch() |