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20.7 kB
| import gradio as gr | |
| import os | |
| import base64 | |
| os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE" | |
| from handle_gradio import ( | |
| process_video, | |
| handle_file_upload, | |
| handle_remove_video, | |
| handle_select_example, | |
| open_modal, | |
| open_modal_for_recording, | |
| close_modal_and_save, | |
| cancel_modal, | |
| open_keypoints_modal, | |
| close_keypoints_modal, | |
| ) | |
| # Check and download the 1GB pre-trained model weights if not cached | |
| print("Checking for large model file...") | |
| local_model_path = os.path.join("Uni_Sign", "unisign_model", "best_checkpoint-wlasl.pth") | |
| if os.path.exists(local_model_path): | |
| model_path = local_model_path | |
| else: | |
| from huggingface_hub import hf_hub_download | |
| model_path = hf_hub_download( | |
| repo_id="plice13/sign-language-weights", | |
| filename="best_checkpoint-wlasl.pth" | |
| ) | |
| print(f"File successfully loaded at: {model_path}") | |
| os.environ["UNISIGN_WEIGHTS"] = model_path | |
| # ==================== | |
| # Prepare base64-encoded logos for header badges from the 'logo' directory | |
| logo_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "logo") | |
| fav_logo_path = os.path.join(logo_dir, "FAV_english_RGB.png") | |
| if not os.path.exists(fav_logo_path): | |
| fav_logo_path = os.path.join(logo_dir, "fav_logo.png") | |
| fav_logo_src = "" | |
| if os.path.exists(fav_logo_path): | |
| with open(fav_logo_path, "rb") as f: | |
| fav_b64 = base64.b64encode(f.read()).decode("utf-8") | |
| fav_logo_src = f"data:image/png;base64,{fav_b64}" | |
| zcu_logo_path = os.path.join(logo_dir, "ZCU_logo_english_RGB.png") | |
| if not os.path.exists(zcu_logo_path): | |
| zcu_logo_path = os.path.join(logo_dir, "zcu_logo.png") | |
| zcu_logo_src = "" | |
| if os.path.exists(zcu_logo_path): | |
| with open(zcu_logo_path, "rb") as f: | |
| zcu_b64 = base64.b64encode(f.read()).decode("utf-8") | |
| zcu_logo_src = f"data:image/png;base64,{zcu_b64}" | |
| # Paths to the 3 example videos from examples/wlasl_new | |
| example_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "examples", "displayed") | |
| example_videos = [ | |
| os.path.join(example_dir, "book.mp4"), | |
| os.path.join(example_dir, "deaf.mp4"), | |
| os.path.join(example_dir, "help.mp4"), | |
| os.path.join(example_dir, "fine.mp4"), | |
| os.path.join(example_dir, "woman.mp4"), | |
| os.path.join(example_dir, "no.mp4"), | |
| ] | |
| # Load CSS from external style.css file | |
| css_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "style.css") | |
| with open(css_path, "r", encoding="utf-8") as f: | |
| custom_css = f.read() | |
| # Information text hardcoded from DELETE/slt_demot.md | |
| INFO_MARKDOWN = """# Sign Language Translation Demo | |
| This interactive demo showcases **automatic sign language translation from video to text**. | |
| The current version demonstrates the processing of **American Sign Language (ASL)** using modern computer vision and deep learning methods. | |
| ## How to use the demo | |
| 1. **Upload a video** or select one of the provided examples. | |
| 2. Click **Submit** to process the video. | |
| 3. The predicted text will be displayed as the output. | |
| For best results, the signer should be clearly visible, including the upper body, hands, and face. | |
| > **Note:** This is a research demonstrator. Predictions may not always be accurate, especially for videos that differ significantly from the data used during training. | |
| ## How does it work? | |
| The system consists of two main stages: **pose preprocessing** and **sign language translation**. | |
| ### Pose preprocessing | |
| The input video is first converted into a structured pose representation. Keypoints describing the signer's **body, hands, and face** are extracted and normalized before being passed to the translation model. | |
| Body keypoints are normalized globally, while hand and facial keypoints are normalized locally to preserve detailed information about their shape and movement. | |
| More information about the preprocessing pipeline is available in the [PoseEstimation repository](https://github.com/JSALT2024/PoseEstimation). | |
| ### Sign language translation | |
| The extracted pose sequence is processed using a model based on **Uni-Sign**, a unified framework for sign language understanding. | |
| More information about the model and our implementation is available in the [Uni-Sign repository](https://github.com/zeleznyt/Uni-Sign). | |
| ## Resources | |
| - [Demo source code](https://github.com/JSALT2024/slt-demo/tree/uni-sign-EP) | |
| - [Pose estimation and preprocessing](https://github.com/JSALT2024/PoseEstimation) | |
| - [Uni-Sign implementation](https://github.com/zeleznyt/Uni-Sign) | |
| - **Uni-Sign:** *Uni-Sign: Toward Unified Sign Language Understanding at Scale*, Li et al., ICLR 2025 | |
| ## Acknowledgements | |
| This demonstrator was developed at the **University of West Bohemia (ZČU), Department of Cybernetics, Computer Vision group**. | |
| Development was supported by the **2026 ZČU internal mini-project programme for the development and wider use of artificial intelligence**. | |
| The system builds upon the **Uni-Sign** framework. We thank its authors and the open-source sign language research community for making their work publicly available. | |
| """ | |
| with gr.Blocks(title="Sign Language Translation", css=custom_css, theme=gr.themes.Default(primary_hue="amber", neutral_hue="neutral")) as app: | |
| current_video = gr.State("") | |
| keypoints_video_state = gr.State("") | |
| with gr.Column(elem_id="main-layout"): | |
| # App Header Row: Left Badge (ZČU Logo), Title & Subtitle, Right Badge (FAV ZČU Logo) | |
| gr.HTML(f""" | |
| <div class="app-header-container"> | |
| <div class="header-badge header-badge-left"> | |
| <a href="https://www.zcu.cz" target="_blank" rel="noopener noreferrer" title="Západočeská univerzita v Plzni"> | |
| <img src="{zcu_logo_src}" alt="Západočeská univerzita v Plzni" class="header-badge-img" /> | |
| </a> | |
| </div> | |
| <div class="header-titles"> | |
| <h1 class="app-title">Sign Language to Text Translation</h1> | |
| <h2 class="app-subtitle">Upload an ASL video and get a text translation.</h2> | |
| </div> | |
| <div class="header-badge header-badge-right"> | |
| <a href="https://fav.zcu.cz" target="_blank" rel="noopener noreferrer" title="Fakulta aplikovaných věd ZČU"> | |
| <img src="{fav_logo_src}" alt="Fakulta aplikovaných věd ZČU" class="header-badge-img" /> | |
| </a> | |
| </div> | |
| </div> | |
| """, elem_classes=["app-header-html"]) | |
| # Card 1: Upload Video Box (Compact Dropzone & Info Row) | |
| with gr.Column(elem_classes=["ui-card"]): | |
| with gr.Row(): | |
| with gr.Column(scale=1, min_width=0): | |
| gr.Markdown("<h3 class='card-title'>Upload video</h3>") | |
| with gr.Column(scale=0, min_width=160, elem_classes=["record-btn-col"]): | |
| record_yourself_btn = gr.Button( | |
| "📹 RECORD YOURSELF", | |
| variant="secondary", | |
| elem_classes=["record-yourself-btn"], | |
| visible=True, | |
| ) | |
| # Compact file dropzone | |
| upload_file = gr.File( | |
| label="Upload Video", | |
| file_types=["video"], | |
| file_count="single", | |
| show_label=False, | |
| elem_classes=["compact-dropzone"] | |
| ) | |
| # Active video status row: Video name on left, action buttons aligned to the right | |
| with gr.Row(visible=False, elem_classes=["video-info-row"]) as video_info_row: | |
| video_name_md = gr.Markdown("<div class='video-name-badge'><span>video.mp4</span></div>", elem_classes=["video-name-col"]) | |
| preview_btn = gr.Button("🎬 Preview & Trim Video", variant="secondary", elem_classes=["preview-modal-btn"]) | |
| change_video_btn = gr.Button("✕ Remove", variant="secondary", elem_classes=["change-vid-btn"]) | |
| # Standalone Translate Action Button (hidden until a video is uploaded or selected) | |
| submit_btn = gr.Button("Translate", variant="primary", elem_classes=["translate-btn"], visible=False) | |
| # Card 2: Translation Result Box (hidden until Translate is clicked) | |
| with gr.Column(elem_classes=["ui-card", "translation-card"], elem_id="translation-card", visible=False) as translation_card: | |
| gr.Markdown("<h3 class='card-title'>Translation</h3>") | |
| translation_display = gr.HTML(value="", elem_id="translation-display", elem_classes=["translation-display-html"]) | |
| show_keypoints_btn = gr.Button( | |
| "🎯 SHOW KEYPOINTS", | |
| variant="secondary", | |
| elem_classes=["show-keypoints-btn"], | |
| visible=False, | |
| ) | |
| # Card 3: Examples Box (6 videos in 3 columns x 2 rows) | |
| with gr.Column(elem_classes=["ui-card"]): | |
| gr.Markdown("<h3 class='card-title'>Examples</h3>") | |
| with gr.Row(elem_classes=["examples-row"]): | |
| with gr.Column(scale=1): | |
| gr.HTML("<div class='example-title'>Book</div>") | |
| gr.Video(value=example_videos[0], interactive=False, show_label=False, autoplay=False, height=160, mirror_webcam=False) | |
| btn_ex1 = gr.Button("Use Example 1", variant="secondary", elem_classes=["example-btn"]) | |
| with gr.Column(scale=1): | |
| gr.HTML("<div class='example-title'>Deaf</div>") | |
| gr.Video(value=example_videos[1], interactive=False, show_label=False, autoplay=False, height=160, mirror_webcam=False) | |
| btn_ex2 = gr.Button("Use Example 2", variant="secondary", elem_classes=["example-btn"]) | |
| with gr.Column(scale=1): | |
| gr.HTML("<div class='example-title'>Help</div>") | |
| gr.Video(value=example_videos[2], interactive=False, show_label=False, autoplay=False, height=160, mirror_webcam=False) | |
| btn_ex3 = gr.Button("Use Example 3", variant="secondary", elem_classes=["example-btn"]) | |
| with gr.Row(elem_classes=["examples-row", "examples-row-second"]): | |
| with gr.Column(scale=1): | |
| gr.HTML("<div class='example-title'>Fine</div>") | |
| gr.Video(value=example_videos[3], interactive=False, show_label=False, autoplay=False, height=160, mirror_webcam=False) | |
| btn_ex4 = gr.Button("Use Example 4", variant="secondary", elem_classes=["example-btn"]) | |
| with gr.Column(scale=1): | |
| gr.HTML("<div class='example-title'>Woman</div>") | |
| gr.Video(value=example_videos[4], interactive=False, show_label=False, autoplay=False, height=160, mirror_webcam=False) | |
| btn_ex5 = gr.Button("Use Example 5", variant="secondary", elem_classes=["example-btn"]) | |
| with gr.Column(scale=1): | |
| gr.HTML("<div class='example-title'>No</div>") | |
| gr.Video(value=example_videos[5], interactive=False, show_label=False, autoplay=False, height=160, mirror_webcam=False) | |
| btn_ex6 = gr.Button("Use Example 6", variant="secondary", elem_classes=["example-btn"]) | |
| # Card 4: Information Box | |
| with gr.Column(elem_classes=["ui-card"]): | |
| gr.Markdown("<h3 class='card-title'>Information</h3>") | |
| gr.Markdown(INFO_MARKDOWN, elem_classes=["info-markdown"]) | |
| # Subtle bottom-right restart session button | |
| with gr.Row(elem_classes=["restart-row"]): | |
| with gr.Column(scale=1): | |
| pass | |
| with gr.Column(scale=0, min_width=140): | |
| restart_btn = gr.Button("🔄 Restart session", variant="secondary", elem_classes=["restart-btn"], size="sm") | |
| # Fullscreen Floating Modal Window for Video Preview & Trimming | |
| with gr.Column(elem_classes=["modal-overlay"], visible=False) as preview_modal: | |
| with gr.Column(elem_classes=["modal-dialog-card"]): | |
| with gr.Row(elem_classes=["modal-header-row"]): | |
| with gr.Column(scale=1, min_width=0): | |
| gr.Markdown("<h3 class='modal-title'>Video Recording, Preview & Trimming</h3>") | |
| with gr.Column(scale=0, min_width=36, elem_classes=["modal-close-col"]): | |
| modal_close_top = gr.Button("✕", size="sm", min_width=36, elem_classes=["modal-close-icon"]) | |
| modal_video = gr.Video( | |
| interactive=True, | |
| show_label=False, | |
| sources=["upload", "webcam"], | |
| mirror_webcam=True, | |
| elem_classes=["modal-video-player"], | |
| ) | |
| with gr.Column(elem_classes=["modal-footer-col"]): | |
| modal_save_btn = gr.Button("✓ Save & Use Video", variant="primary", elem_classes=["modal-done-btn"]) | |
| # Fullscreen Floating Modal Window for Keypoints Visualization | |
| with gr.Column(elem_classes=["modal-overlay", "keypoints-modal-overlay"], visible=False) as keypoints_modal: | |
| with gr.Column(elem_classes=["modal-dialog-card"]): | |
| with gr.Row(elem_classes=["modal-header-row"]): | |
| with gr.Column(scale=1, min_width=0): | |
| gr.Markdown("<h3 class='modal-title'>🎯 Extracted Pose & Keypoints</h3>") | |
| with gr.Column(scale=0, min_width=36, elem_classes=["modal-close-col"]): | |
| keypoints_close_top = gr.Button("✕", size="sm", min_width=36, elem_classes=["modal-close-icon"]) | |
| keypoints_modal_video = gr.Video( | |
| interactive=False, | |
| show_label=False, | |
| autoplay=True, | |
| loop=True, | |
| elem_classes=["modal-video-player", "keypoints-video-player"], | |
| ) | |
| with gr.Column(elem_classes=["modal-footer-col"]): | |
| keypoints_close_bottom = gr.Button("Close", variant="secondary", elem_classes=["modal-done-btn"]) | |
| def start_translating_ui(): | |
| spinner_html = """<div class="translation-content-box"><div class="loading-container"><div class="pulse-spinner"></div></div></div>""" | |
| return gr.update(visible=True), spinner_html, gr.update(visible=False), "" | |
| def finish_translating(video_path, progress=gr.Progress()): | |
| if not video_path: | |
| err_html = """<div class="translation-content-box"><div style="color: #dba70e; font-weight: 600; font-size: 15px; text-align: center;">Please select or upload a video first.</div></div>""" | |
| return err_html, gr.update(visible=False), "" | |
| try: | |
| trans_result, kp_video = process_video(video_path, progress=progress) | |
| except Exception as e: | |
| err_html = f"""<div class="translation-content-box"><div style="color: #ff6b6b; font-weight: 600; font-size: 14px; text-align: center;">Error: {e}</div></div>""" | |
| return err_html, gr.update(visible=False), "" | |
| clean_result = str(trans_result).strip() | |
| if clean_result.startswith("Error") or "error" in clean_result.lower(): | |
| err_html = f"""<div class="translation-content-box"><div style="color: #ff6b6b; font-weight: 600; font-size: 14px; text-align: center;">{clean_result}</div></div>""" | |
| return err_html, gr.update(visible=False), "" | |
| content_html = f"""<div class="translation-content-box"><div class="translation-text">{clean_result}</div></div>""" | |
| has_kp = bool(kp_video and os.path.exists(kp_video)) | |
| return content_html, gr.update(visible=has_kp), kp_video if has_kp else "" | |
| # Upload file event | |
| upload_file.upload( | |
| fn=handle_file_upload, | |
| inputs=upload_file, | |
| outputs=[current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| ) | |
| # Remove / Change video event | |
| change_video_btn.click( | |
| fn=handle_remove_video, | |
| inputs=None, | |
| outputs=[current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| ) | |
| # Smooth scroll to top JavaScript helper for example selections | |
| scroll_top_js = "() => { window.scrollTo({ top: 0, behavior: 'smooth' }); }" | |
| # Examples click events with smooth auto-scroll to top | |
| btn_ex1.click( | |
| fn=lambda: handle_select_example(example_videos[0]), | |
| inputs=None, | |
| outputs=[current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| js=scroll_top_js, | |
| ) | |
| btn_ex2.click( | |
| fn=lambda: handle_select_example(example_videos[1]), | |
| inputs=None, | |
| outputs=[current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| js=scroll_top_js, | |
| ) | |
| btn_ex3.click( | |
| fn=lambda: handle_select_example(example_videos[2]), | |
| inputs=None, | |
| outputs=[current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| js=scroll_top_js, | |
| ) | |
| btn_ex4.click( | |
| fn=lambda: handle_select_example(example_videos[3]), | |
| inputs=None, | |
| outputs=[current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| js=scroll_top_js, | |
| ) | |
| btn_ex5.click( | |
| fn=lambda: handle_select_example(example_videos[4]), | |
| inputs=None, | |
| outputs=[current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| js=scroll_top_js, | |
| ) | |
| btn_ex6.click( | |
| fn=lambda: handle_select_example(example_videos[5]), | |
| inputs=None, | |
| outputs=[current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| js=scroll_top_js, | |
| ) | |
| # Open Modal event from Preview & Trim button | |
| preview_btn.click( | |
| fn=open_modal, | |
| inputs=current_video, | |
| outputs=[preview_modal, modal_video], | |
| ) | |
| # Open Modal event from Record Yourself button | |
| record_yourself_btn.click( | |
| fn=open_modal_for_recording, | |
| inputs=None, | |
| outputs=[preview_modal, modal_video], | |
| ) | |
| # Restart / Reset Session event | |
| restart_btn.click( | |
| fn=handle_remove_video, | |
| inputs=None, | |
| outputs=[current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| js="() => { window.location.href = window.location.href.split('#')[0]; }" | |
| ) | |
| # Save & Use Video | |
| modal_save_btn.click( | |
| fn=close_modal_and_save, | |
| inputs=[modal_video, current_video], | |
| outputs=[preview_modal, current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| ) | |
| # Close / Cancel Modal event | |
| modal_close_top.click( | |
| fn=cancel_modal, | |
| inputs=current_video, | |
| outputs=[preview_modal, current_video, upload_file, record_yourself_btn, video_info_row, video_name_md, submit_btn, translation_card, modal_video], | |
| ) | |
| # Translate event | |
| submit_btn.click( | |
| fn=start_translating_ui, | |
| inputs=None, | |
| outputs=[translation_card, translation_display, show_keypoints_btn, keypoints_video_state], | |
| ).then( | |
| fn=finish_translating, | |
| inputs=current_video, | |
| outputs=[translation_display, show_keypoints_btn, keypoints_video_state], | |
| ) | |
| # Open Keypoints Modal | |
| show_keypoints_btn.click( | |
| fn=open_keypoints_modal, | |
| inputs=keypoints_video_state, | |
| outputs=[keypoints_modal, keypoints_modal_video], | |
| ) | |
| # Close Keypoints Modal | |
| keypoints_close_top.click( | |
| fn=close_keypoints_modal, | |
| inputs=None, | |
| outputs=[keypoints_modal, keypoints_modal_video], | |
| ) | |
| keypoints_close_bottom.click( | |
| fn=close_keypoints_modal, | |
| inputs=None, | |
| outputs=[keypoints_modal, keypoints_modal_video], | |
| ) | |
| if __name__ == "__main__": | |
| app.queue(default_concurrency_limit=1).launch() | |