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| import gradio as gr | |
| from askui_ml_helper.utils.pta_text import PtaTextInference | |
| def main(): | |
| inference = PtaTextInference("model/pta-text-v0.1.pt") | |
| # Gradio Interface | |
| iface = gr.Interface( | |
| fn=inference.process_image_and_draw_circle, | |
| inputs=[gr.Image(type="pil", label = "Upload Image"), | |
| gr.Textbox(label = "Prompt", placeholder='Enter a prompt to find in the image', value='click on the text "Login"'), | |
| gr.Slider(minimum=5, maximum=20, value=10, label="Prediction Dot Size", step=5), | |
| gr.Checkbox(label="Resize (Recommended)", value=True, info="Resize the image to 1920x1080 for better results?")], | |
| outputs=gr.Image(type="pil"), | |
| title="PTA-Text: A **Text-only** Click Model", | |
| description="Based on PTA-text ([Huggingface model card](https://huggingface.co/AskUI/pta-text-0.1) ).PTA is a small part of our bigger model - PTA-1 (Prompt-To-Automation). \nInstructions: Upload a UI image and enter a text finding prompt to see the model's prediction. \nLimitations: Currently, limited to single screen images.", | |
| examples=[["./sample.png", "click on the text 'Like'", 10, True], | |
| ["./sample.png", "click on 'Submit' Retry for free!", 15, True]] | |
| ) | |
| iface.launch(server_name="0.0.0.0") | |
| if __name__ == "__main__": | |
| main() | |