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| import argparse | |
| import gradio as gr | |
| from common.utils import ( | |
| matcher_zoo, | |
| change_estimate_geom, | |
| run_matching, | |
| ransac_zoo, | |
| gen_examples, | |
| ) | |
| DESCRIPTION = """ | |
| # Image Matching WebUI | |
| This Space demonstrates [Image Matching WebUI](https://github.com/Vincentqyw/image-matching-webui) by vincent qin. Feel free to play with it, or duplicate to run image matching without a queue! | |
| 🔎 For more details about supported local features and matchers, please refer to https://github.com/Vincentqyw/image-matching-webui | |
| 🚀 All algorithms run on CPU for inference on HF, causing slow speeds and high latency. For faster inference, please download the [source code](https://github.com/Vincentqyw/image-matching-webui) for local deployment or check [openxlab space](https://github.com/Vincentqyw/image-matching-webui) and [direct URL](https://g-app-center-083997-7409-n9elr1.openxlab.space) | |
| 🐛 Your feedback is valuable to me. Please do not hesitate to report any bugs [here](https://github.com/Vincentqyw/image-matching-webui/issues). | |
| """ | |
| def ui_change_imagebox(choice): | |
| return {"value": None, "source": choice, "__type__": "update"} | |
| def ui_reset_state( | |
| image0, | |
| image1, | |
| match_threshold, | |
| extract_max_keypoints, | |
| keypoint_threshold, | |
| key, | |
| # enable_ransac=False, | |
| ransac_method="RANSAC", | |
| ransac_reproj_threshold=8, | |
| ransac_confidence=0.999, | |
| ransac_max_iter=10000, | |
| choice_estimate_geom="Homography", | |
| ): | |
| match_threshold = 0.2 | |
| extract_max_keypoints = 1000 | |
| keypoint_threshold = 0.015 | |
| key = list(matcher_zoo.keys())[0] | |
| image0 = None | |
| image1 = None | |
| # enable_ransac = False | |
| return ( | |
| image0, | |
| image1, | |
| match_threshold, | |
| extract_max_keypoints, | |
| keypoint_threshold, | |
| key, | |
| ui_change_imagebox("upload"), | |
| ui_change_imagebox("upload"), | |
| "upload", | |
| None, # keypoints | |
| None, # raw matches | |
| None, # ransac matches | |
| {}, | |
| {}, | |
| None, | |
| {}, | |
| # False, | |
| "RANSAC", | |
| 8, | |
| 0.999, | |
| 10000, | |
| "Homography", | |
| ) | |
| # "footer {visibility: hidden}" | |
| def run(config): | |
| with gr.Blocks(css="style.css") as app: | |
| gr.Markdown(DESCRIPTION) | |
| with gr.Row(equal_height=False): | |
| with gr.Column(): | |
| with gr.Row(): | |
| matcher_list = gr.Dropdown( | |
| choices=list(matcher_zoo.keys()), | |
| value="disk+lightglue", | |
| label="Matching Model", | |
| interactive=True, | |
| ) | |
| match_image_src = gr.Radio( | |
| ["upload", "webcam", "canvas"], | |
| label="Image Source", | |
| value="upload", | |
| ) | |
| with gr.Row(): | |
| input_image0 = gr.Image( | |
| label="Image 0", | |
| type="numpy", | |
| interactive=True, | |
| image_mode="RGB", | |
| ) | |
| input_image1 = gr.Image( | |
| label="Image 1", | |
| type="numpy", | |
| interactive=True, | |
| image_mode="RGB", | |
| ) | |
| with gr.Row(): | |
| button_reset = gr.Button(value="Reset") | |
| button_run = gr.Button( | |
| value="Run Match", variant="primary" | |
| ) | |
| with gr.Accordion("Advanced Setting", open=False): | |
| with gr.Accordion("Matching Setting", open=True): | |
| with gr.Row(): | |
| match_setting_threshold = gr.Slider( | |
| minimum=0.0, | |
| maximum=1, | |
| step=0.001, | |
| label="Match thres.", | |
| value=0.1, | |
| ) | |
| match_setting_max_features = gr.Slider( | |
| minimum=10, | |
| maximum=10000, | |
| step=10, | |
| label="Max features", | |
| value=1000, | |
| ) | |
| # TODO: add line settings | |
| with gr.Row(): | |
| detect_keypoints_threshold = gr.Slider( | |
| minimum=0, | |
| maximum=1, | |
| step=0.001, | |
| label="Keypoint thres.", | |
| value=0.015, | |
| ) | |
| detect_line_threshold = gr.Slider( | |
| minimum=0.1, | |
| maximum=1, | |
| step=0.01, | |
| label="Line thres.", | |
| value=0.2, | |
| ) | |
| # matcher_lists = gr.Radio( | |
| # ["NN-mutual", "Dual-Softmax"], | |
| # label="Matcher mode", | |
| # value="NN-mutual", | |
| # ) | |
| with gr.Accordion("RANSAC Setting", open=True): | |
| with gr.Row(equal_height=False): | |
| # enable_ransac = gr.Checkbox(label="Enable RANSAC") | |
| ransac_method = gr.Dropdown( | |
| choices=ransac_zoo.keys(), | |
| value="RANSAC", | |
| label="RANSAC Method", | |
| interactive=True, | |
| ) | |
| ransac_reproj_threshold = gr.Slider( | |
| minimum=0.0, | |
| maximum=12, | |
| step=0.01, | |
| label="Ransac Reproj threshold", | |
| value=8.0, | |
| ) | |
| ransac_confidence = gr.Slider( | |
| minimum=0.0, | |
| maximum=1, | |
| step=0.00001, | |
| label="Ransac Confidence", | |
| value=0.99999, | |
| ) | |
| ransac_max_iter = gr.Slider( | |
| minimum=0.0, | |
| maximum=100000, | |
| step=100, | |
| label="Ransac Iterations", | |
| value=10000, | |
| ) | |
| with gr.Accordion("Geometry Setting", open=False): | |
| with gr.Row(equal_height=False): | |
| # show_geom = gr.Checkbox(label="Show Geometry") | |
| choice_estimate_geom = gr.Radio( | |
| ["Fundamental", "Homography"], | |
| label="Reconstruct Geometry", | |
| value="Homography", | |
| ) | |
| # with gr.Column(): | |
| # collect inputs | |
| inputs = [ | |
| input_image0, | |
| input_image1, | |
| match_setting_threshold, | |
| match_setting_max_features, | |
| detect_keypoints_threshold, | |
| matcher_list, | |
| # enable_ransac, | |
| ransac_method, | |
| ransac_reproj_threshold, | |
| ransac_confidence, | |
| ransac_max_iter, | |
| choice_estimate_geom, | |
| ] | |
| # Add some examples | |
| with gr.Row(): | |
| # Example inputs | |
| gr.Examples( | |
| examples=gen_examples(), | |
| inputs=inputs, | |
| outputs=[], | |
| fn=run_matching, | |
| cache_examples=False, | |
| label=( | |
| "Examples (click one of the images below to Run" | |
| " Match)" | |
| ), | |
| ) | |
| with gr.Accordion("Open for More!", open=False): | |
| gr.Markdown( | |
| f""" | |
| <h3>Supported Algorithms</h3> | |
| {", ".join(matcher_zoo.keys())} | |
| """ | |
| ) | |
| with gr.Column(): | |
| output_keypoints = gr.Image(label="Keypoints", type="numpy") | |
| output_matches_raw = gr.Image(label="Raw Matches", type="numpy") | |
| output_matches_ransac = gr.Image( | |
| label="Ransac Matches", type="numpy" | |
| ) | |
| with gr.Accordion( | |
| "Open for More: Matches Statistics", open=False | |
| ): | |
| matches_result_info = gr.JSON(label="Matches Statistics") | |
| matcher_info = gr.JSON(label="Match info") | |
| with gr.Accordion("Open for More: Warped Image", open=False): | |
| output_wrapped = gr.Image( | |
| label="Wrapped Pair", type="numpy" | |
| ) | |
| with gr.Accordion("Open for More: Geometry info", open=False): | |
| geometry_result = gr.JSON(label="Reconstructed Geometry") | |
| # callbacks | |
| match_image_src.change( | |
| fn=ui_change_imagebox, | |
| inputs=match_image_src, | |
| outputs=input_image0, | |
| ) | |
| match_image_src.change( | |
| fn=ui_change_imagebox, | |
| inputs=match_image_src, | |
| outputs=input_image1, | |
| ) | |
| # collect outputs | |
| outputs = [ | |
| output_keypoints, | |
| output_matches_raw, | |
| output_matches_ransac, | |
| matches_result_info, | |
| matcher_info, | |
| geometry_result, | |
| output_wrapped, | |
| ] | |
| # button callbacks | |
| button_run.click(fn=run_matching, inputs=inputs, outputs=outputs) | |
| # Reset images | |
| reset_outputs = [ | |
| input_image0, | |
| input_image1, | |
| match_setting_threshold, | |
| match_setting_max_features, | |
| detect_keypoints_threshold, | |
| matcher_list, | |
| input_image0, | |
| input_image1, | |
| match_image_src, | |
| output_keypoints, | |
| output_matches_raw, | |
| output_matches_ransac, | |
| matches_result_info, | |
| matcher_info, | |
| output_wrapped, | |
| geometry_result, | |
| # enable_ransac, | |
| ransac_method, | |
| ransac_reproj_threshold, | |
| ransac_confidence, | |
| ransac_max_iter, | |
| choice_estimate_geom, | |
| ] | |
| button_reset.click( | |
| fn=ui_reset_state, inputs=inputs, outputs=reset_outputs | |
| ) | |
| # estimate geo | |
| choice_estimate_geom.change( | |
| fn=change_estimate_geom, | |
| inputs=[ | |
| input_image0, | |
| input_image1, | |
| geometry_result, | |
| choice_estimate_geom, | |
| ], | |
| outputs=[output_wrapped, geometry_result], | |
| ) | |
| app.queue().launch(share=False) | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument( | |
| "--config_path", | |
| type=str, | |
| default="config.yaml", | |
| help="configuration file path", | |
| ) | |
| args = parser.parse_args() | |
| config = None | |
| run(config) | |