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| import gradio as gr | |
| from PIL import Image | |
| from toxic_detection import TextToxicDetector | |
| from toxic_detection import ImgToxicDetector | |
| text_model = TextToxicDetector() | |
| text_model.load('szzzzz/xlm-roberta-base-text-toxic') | |
| img_model = ImgToxicDetector() | |
| img_model.load('./toxic_detection_res50.gz.tar') | |
| def image_toxic_detect(im): | |
| return img_model.detect(Image.fromarray(im)) | |
| def text_toxic_detect(text): | |
| print(text) | |
| return text_model.detect(text) | |
| with gr.Blocks() as app: | |
| gr.Markdown("Toxic Detection") | |
| with gr.Tab("Toxic Text Detector"): | |
| text_input_toxic = gr.Textbox() | |
| text_output_toxic = gr.Label(num_top_classes=1) | |
| text_button_toxic = gr.Button("text_toxic") | |
| with gr.Tab("Toxic Image Detector"): | |
| image_input_toxic = gr.Image() | |
| image_output_toxic = gr.Label(num_top_classes=2) | |
| image_button_toxic = gr.Button("image_toxic") | |
| text_button_toxic.click(text_toxic_detect, inputs=text_input_toxic, outputs=text_output_toxic) | |
| image_button_toxic.click(image_toxic_detect, inputs=image_input_toxic, outputs=image_output_toxic) | |
| app.launch(server_name="0.0.0.0") | |