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| import gradio as gr | |
| from main_func import video_identity | |
| with gr.Blocks() as demo: | |
| with gr.Row(variant='compact'): | |
| with gr.Column(): | |
| gr.Markdown("#### Dynamic Time Warping:") | |
| with gr.Row(variant='compact'): | |
| dtw_mean = gr.Slider( | |
| value=0.4, | |
| minimum=0, | |
| maximum=1.0, | |
| step=0.05, | |
| label="Winsorized Mean" | |
| ) | |
| dtw_filter = gr.Slider( | |
| value=13, | |
| minimum=1, | |
| maximum=20, | |
| step=1, | |
| label="Savitzky-Golay Filter" | |
| ) | |
| gr.Markdown("#### Thresholds:") | |
| with gr.Row(variant='compact'): | |
| angles_sensitive = gr.Number( | |
| value=15, | |
| minimum=0, | |
| maximum=75, | |
| step=1, | |
| min_width=100, | |
| label="Sensitive" | |
| ) | |
| angles_common = gr.Number( | |
| value=30, | |
| minimum=0, | |
| maximum=75, | |
| step=1, | |
| min_width=100, | |
| label="Standart" | |
| ) | |
| angles_insensitive = gr.Number( | |
| value=55, | |
| minimum=0, | |
| maximum=75, | |
| step=1, | |
| min_width=100, | |
| label="Insensitive" | |
| ) | |
| gr.Markdown("#### Patience:") | |
| trigger_state = gr.Radio(value="one", choices=["one", "two", "three"], label="Trigger Count") | |
| gr.Markdown("#### Plot arrows:") | |
| show_arrows = gr.Checkbox(label="If True, arrows will be plotted on the video") | |
| input_teacher = gr.Video(show_share_button=False, show_download_button=False, sources=["upload"], label="Teacher's Video") | |
| input_student = gr.Video(show_share_button=False, show_download_button=False, sources=["upload"], label="Student's Video") | |
| with gr.Accordion("Usage:", open=False): | |
| with gr.Accordion("Application purpose:", open=False): | |
| gr.Markdown(""" | |
| This application is designed to compare a professional dancer's performance with that of a student, identifying the student's incorrect movements relative to the professional. | |
| Key features: | |
| 1. Accepts two dance videos as input: one of a professional dancer and one of a student. | |
| 2. Aligns the movements of both dancers, even if they perform at different rhythms. | |
| 3. Generates a single concatenated video showing the aligned movements of both dancers side-by-side. | |
| 4. Highlights the student's errors for easy identification. | |
| 5. Produces a text log of errors with corresponding timestamps. | |
| This tool offering a detailed analysis of technique and areas for improvement. | |
| """) | |
| with gr.Accordion("Video formats:", open=False): | |
| gr.Markdown(""" | |
| For the input video to be playable in the browser, it must have a compatible container and codec combination. | |
| Allowed combinations are: | |
| - **.mp4** with **H.264** codec | |
| - **.ogg** with **Theora** codec | |
| - **.webm** with **VP9** codec | |
| If the component detects that the output video would not be playable in the browser, it will attempt to convert it to a playable **.mp4** video. | |
| The output video format is always **.mp4**, which is playable in the browser. The resolution of the output concatenated video is **2560x720**. | |
| """) | |
| with gr.Accordion("Settings clarifications:", open=False): | |
| with gr.Accordion("Dynamic Time Warping:", open=False): | |
| gr.Markdown(""" | |
| Dynamic Time Warping is an algorithm that performs frame-by-frame alignment for videos with different speeds. | |
| - **Winsorized mean**: Determines the portion of DTW paths, sorted from best to worst, to use for generating the mean DTW alignment. Reasonable values range from 0.25 to 0.6. | |
| - **Savitzky-Golay Filter**: Enhances the capabilities of the Winsorized mean, making DTW alignment more similar to a strict line. Reasonable values range from 2 to 10. | |
| """) | |
| with gr.Accordion("Thresholds:", open=False): | |
| gr.Markdown(""" | |
| Thresholds are used to identify student errors in dance. If the difference in angle between the teacher's and student's videos exceeds this threshold, it is counted as an error. | |
| - **Sensitive**: A threshold that is currently not used. | |
| - **Standard**: A threshold for most angles. Reasonable values range from 20 to 40. | |
| - **Insensitive**: A threshold for difficult areas, such as hands and toes. Reasonable values range from 35 to 55. | |
| """) | |
| with gr.Accordion("Patience:", open=False): | |
| gr.Markdown(""" | |
| Patience settings help prevent model errors by highlighting only those errors detected in consecutive frames. | |
| Options: | |
| - **One**: Utilizes 1 consecutive frame for error detection. | |
| - **Two**: Utilizes 2 consecutive frames for error detection. | |
| - **Three**: Utilizes 3 consecutive frames for error detection. | |
| Guidelines: | |
| - Option **One** is better for fast dances and videos with low frame rates. | |
| - Option **Three** is better for slow dances and videos with high frame rates. | |
| - Option **Two** provides intermediate performance and can be used for experimentation. | |
| The patience setting allows you to balance between sensitivity and accuracy in error detection, depending on the dance style and video quality. | |
| """) | |
| with gr.Row(): | |
| gr_button = gr.Button("Run Pose Comparison") | |
| with gr.Row(): | |
| gr.HTML("<div style='height: 100px;'></div>") | |
| with gr.Row(): | |
| output_merged = gr.Video(show_download_button=True) | |
| with gr.Row(): | |
| general_log = gr.TextArea(lines=10, label="Error log", scale=3) | |
| text_log=gr.File(label="Download logs and settings", scale=1) | |
| gr_button.click( | |
| fn=video_identity, | |
| inputs=[dtw_mean, dtw_filter, angles_sensitive, angles_common, angles_insensitive, trigger_state, show_arrows, input_teacher, input_student], | |
| outputs=[output_merged, general_log, text_log] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |