mayukhdeb/devolearn-instance-segmentation-demo
0
1import gradio as gr2from demo import automask_image_app, automask_video_app, sahi_autoseg_app3 4 5def image_app():6 with gr.Blocks():7 with gr.Row():8 with gr.Column():9 seg_automask_image_file = gr.Image(type="filepath").style(height=260)10 with gr.Row():11 with gr.Column():12 seg_automask_image_model_type = gr.Dropdown(13 choices=[14 "vit_h",15 "vit_l",16 "vit_b",17 ],18 value="vit_l",19 label="Model Type",20 )21 22 seg_automask_image_min_area = gr.Number(23 value=0,24 label="Min Area",25 )26 with gr.Row():27 with gr.Column():28 seg_automask_image_points_per_side = gr.Slider(29 minimum=0,30 maximum=32,31 step=2,32 value=16,33 label="Points per Side",34 )35 36 seg_automask_image_points_per_batch = gr.Slider(37 minimum=0,38 maximum=64,39 step=2,40 value=64,41 label="Points per Batch",42 )43 44 seg_automask_image_predict = gr.Button(value="Generator")45 46 with gr.Column():47 output_image = gr.Image()48 49 seg_automask_image_predict.click(50 fn=automask_image_app,51 inputs=[52 seg_automask_image_file,53 seg_automask_image_model_type,54 seg_automask_image_points_per_side,55 seg_automask_image_points_per_batch,56 seg_automask_image_min_area,57 ],58 outputs=[output_image],59 )60 61 62def video_app():63 with gr.Blocks():64 with gr.Row():65 with gr.Column():66 seg_automask_video_file = gr.Video().style(height=260)67 with gr.Row():68 with gr.Column():69 seg_automask_video_model_type = gr.Dropdown(70 choices=[71 "vit_h",72 "vit_l",73 "vit_b",74 ],75 value="vit_l",76 label="Model Type",77 )78 seg_automask_video_min_area = gr.Number(79 value=1000,80 label="Min Area",81 )82 83 with gr.Row():84 with gr.Column():85 seg_automask_video_points_per_side = gr.Slider(86 minimum=0,87 maximum=32,88 step=2,89 value=16,90 label="Points per Side",91 )92 93 seg_automask_video_points_per_batch = gr.Slider(94 minimum=0,95 maximum=64,96 step=2,97 value=64,98 label="Points per Batch",99 )100 101 seg_automask_video_predict = gr.Button(value="Generator")102 with gr.Column():103 output_video = gr.Video()104 105 seg_automask_video_predict.click(106 fn=automask_video_app,107 inputs=[108 seg_automask_video_file,109 seg_automask_video_model_type,110 seg_automask_video_points_per_side,111 seg_automask_video_points_per_batch,112 seg_automask_video_min_area,113 ],114 outputs=[output_video],115 )116 117 118def sahi_app():119 with gr.Blocks():120 with gr.Row():121 with gr.Column():122 sahi_image_file = gr.Image(type="filepath").style(height=260)123 sahi_autoseg_model_type = gr.Dropdown(124 choices=[125 "vit_h",126 "vit_l",127 "vit_b",128 ],129 value="vit_l",130 label="Sam Model Type",131 )132 133 with gr.Row():134 with gr.Column():135 sahi_model_type = gr.Dropdown(136 choices=[137 "yolov5",138 "yolov8",139 ],140 value="yolov5",141 label="Detector Model Type",142 )143 sahi_image_size = gr.Slider(144 minimum=0,145 maximum=1600,146 step=32,147 value=640,148 label="Image Size",149 ) 150 151 sahi_overlap_width = gr.Slider(152 minimum=0,153 maximum=1,154 step=0.1,155 value=0.2,156 label="Overlap Width",157 )158 159 sahi_slice_width = gr.Slider(160 minimum=0,161 maximum=640,162 step=32,163 value=256,164 label="Slice Width",165 )166 167 with gr.Row():168 with gr.Column(): 169 sahi_model_path = gr.Dropdown(170 choices=[171 "yolov5l.pt",172 "yolov5l6.pt",173 "yolov8l.pt",174 "yolov8x.pt"175 ],176 value="yolov5l6.pt",177 label="Detector Model Path",178 )179 180 sahi_conf_th = gr.Slider(181 minimum=0,182 maximum=1,183 step=0.1,184 value=0.2,185 label="Confidence Threshold",186 ) 187 sahi_overlap_height = gr.Slider(188 minimum=0,189 maximum=1,190 step=0.1,191 value=0.2,192 label="Overlap Height",193 )194 sahi_slice_height = gr.Slider(195 minimum=0,196 maximum=640,197 step=32,198 value=256,199 label="Slice Height",200 )201 sahi_image_predict = gr.Button(value="Generator")202 203 with gr.Column():204 output_image = gr.Image()205 206 sahi_image_predict.click(207 fn=sahi_autoseg_app,208 inputs=[209 sahi_image_file,210 sahi_autoseg_model_type,211 sahi_model_type,212 sahi_model_path,213 sahi_conf_th,214 sahi_image_size,215 sahi_slice_height,216 sahi_slice_width,217 sahi_overlap_height,218 sahi_overlap_width,219 220 ],221 outputs=[output_image],222 )223 224def metaseg_app():225 app = gr.Blocks()226 with app:227 with gr.Row():228 with gr.Column():229 with gr.Tab("Image"):230 image_app()231 with gr.Tab("Video"):232 video_app()233 with gr.Tab("SAHI"):234 sahi_app()235 236 237 app.queue(concurrency_count=1)238 app.launch(debug=True, enable_queue=True, share=True)239 240 241if __name__ == "__main__":242 metaseg_app()243