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 """ 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(label="Reset", value="Reset") button_run = gr.Button( label="Run Match", 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"""

Supported Algorithms

{", ".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)