import gradio as gr # Gradio package for interface import sys # System package for path dependencies sys.path.append('Interface_Dependencies') sys.path.append('Engineering-Clinic-Emerging-AI-Design-Interface/Interface_Dependencies') sys.path.append('Engineering-Clinic-Emerging-AI-Design-Interface/yolov7-main') sys.path.append('./') # to run '$ python *.py' files in subdirectories from run_methods import run_image, run_video, correct_video, run_stream # Gradio Interface Code with gr.Blocks(title="YOLO7 Interface",theme=gr.themes.Base()) as demo: gr.Markdown( """ # Image & Video Interface for YOLO7 Model Upload your own image or video and watch YOLO7 try to guess what it is! """) # For for input & output settings with gr.Row() as file_settings: # Allows choice for uploading image or video [for all] file_type = gr.Radio(label="File Type",info="Choose 'Image' if you are uploading an image, Choose 'Video' if you are uploading a video", choices=['Image','Video'],value='Image',show_label=True,interactive=True) # Allows choice of source, from computer or webcam [for all] source_type = gr.Radio(label="Source Type",info="Choose 'Computer' if you are uploading from your computer, Choose 'Webcam' if you would like to use your webcam", choices=['Computer','Webcam'],value='Computer',show_label=True,interactive=True) # Allows choice of which convolutional layer to show (1-17) [only for images] conv_layer = gr.Slider(label="Convolution Layer",info="Choose a whole number from 1 to 17 to see the corresponding convolutional layer", minimum=1,maximum=17,value=1,interactive=True,step=1,show_label=True) # Allows choice if video from webcam is streaming or uploaded [only for videos] video_stream = gr.Checkbox(label="Stream from webcam?",info="Check this box if you would like to stream from your webcam",value=False,show_label=True,interactive=True,visible=False) # Allows choice of which smooth gradient output to show (1-3) [only for images] output_map = gr.Slider(label="Map Output Number",info="Choose a whole number from 1 to 3 to see the corresponding attribution map", minimum=1,maximum=3,value=1,interactive=True,step=1,show_label=True) # For video inputs & outputs with gr.Row(visible=False) as vid_tot_row: # For webcam video inputs with gr.Row(visible=False) as vid_web_row: # For webcam video input vid_web_input = gr.Video(label="Input Video",source="webcam",show_share_button=True,interactive=True) # For webcam streaming input vid_streaming = gr.Image(type='pil',source="webcam",label="Input Image",streaming=False,visible=False,interactive=True) # For computer video inputs with gr.Row() as vid_com_row: # For computer video input vid_com_input = gr.Video(source="upload",label="Input Video",show_share_button=True,interactive=True) # For video output vid_output = gr.Video(label="Output Video",show_share_button=True) with gr.Row() as im_tot_row: with gr.Row(visible=False) as im_web_row: im_web_input = gr.Image(type='pil',source="webcam",label="Input Image") with gr.Row() as im_com_row: im_com_input = gr.Image(source="upload",type='filepath',label="Input Image",show_download_button=True,show_share_button=True,interactive=True) with gr.Row() as im_out_row: im_output = gr.Image(type='filepath',label="Output Image",show_download_button=True,show_share_button=True,interactive=False, visible=True) im_conv_output = gr.Image(type='filepath',label="Output Convolution",show_download_button=True,show_share_button=True,interactive=False) im_smooth_output = gr.Image(type='filepath',label="Output Smooth Gradient",show_download_button=True,show_share_button=True,interactive=False) labels = gr.Textbox(label='Top Predictions:', value = "") #ME formatted_time = gr.Textbox(label = 'Time to Run in Seconds:', value = "") with gr.Row(visible=False) as vid_tot_start: with gr.Row(visible=False) as vid_web_start: vid_web_but = gr.Button(label="Start") gr.ClearButton(components=[vid_web_input, vid_output], interactive=True, visible=True) with gr.Row(visible=False) as vid_com_start: vid_com_but = gr.Button(label="Start") gr.ClearButton(components=[vid_com_input, vid_output], interactive=True, visible=True) with gr.Row() as im_tot_start: with gr.Row(visible=False) as im_web_start: im_web_but = gr.Button(label="Start") gr.ClearButton(components=[im_web_input, im_output, im_conv_output, im_smooth_output, labels, formatted_time], #Added info interactive=True, visible=True) with gr.Row() as im_com_start: im_com_but = gr.Button(label="Start") gr.ClearButton(components=[im_com_input, im_output, im_conv_output, im_smooth_output, labels, formatted_time], #Added info interactive=True, visible=True) with gr.Row() as settings: inf_size = gr.Number(label='Inference Size (pixels)',value=640,precision=0) obj_conf_thr = gr.Number(label='Object Confidence Threshold',value=0.25) iou_thr = gr.Number(label='IOU threshold for NMS',value=0.45) agnostic_nms = gr.Checkbox(label='Agnostic NMS',value=True) norm = gr.Checkbox(label='Normalize Gradient',value=False) def change_file_type(file, source, is_stream): """ Changes the visible components of the gradio interface Args: file (str): Type of the file (image or video) source (str): If the file is uploaded or from webcam Returns: Dictionary: Each component of the interface that needs to be updated. """ if file == "Image": if source == "Computer": return { im_tot_row: gr.Row.update(visible=True), vid_tot_row: gr.Row.update(visible=False), im_tot_start: gr.Row.update(visible=True), vid_tot_start: gr.Row.update(visible=False), vid_com_row: gr.Row.update(visible=False), vid_web_row: gr.Row.update(visible=False), im_com_row: gr.Row.update(visible=True), im_web_row: gr.Row.update(visible=False), vid_web_start: gr.Row.update(visible=False), vid_com_start: gr.Row.update(visible=False), im_web_start: gr.Row.update(visible=False), im_com_start: gr.Row.update(visible=True), conv_layer: gr.Slider(visible=True), video_stream: gr.Checkbox(visible=False, value=False), vid_streaming: gr.Image(visible=False, streaming=False), vid_web_input: gr.Video(visible=True), im_out_row: gr.Row.update(visible=True), im_conv_output: gr.Image(visible=True), im_smooth_output: gr.Image(visible=True), vid_output: gr.Video(visible=False), output_map: gr.Slider(visible=True) } else: return { im_tot_row: gr.Row.update(visible=True), vid_tot_row: gr.Row.update(visible=False), im_tot_start: gr.Row.update(visible=True), vid_tot_start: gr.Row.update(visible=False), vid_com_row: gr.Row.update(visible=False), vid_web_row: gr.Row.update(visible=False), im_com_row: gr.Row.update(visible=False), im_web_row: gr.Row.update(visible=True), vid_web_start: gr.Row.update(visible=False), vid_com_start: gr.Row.update(visible=False), im_web_start: gr.Row.update(visible=True), im_com_start: gr.Row.update(visible=False), conv_layer: gr.Slider(visible=True), video_stream: gr.Checkbox(visible=False, value=False), vid_streaming: gr.Image(visible=False, streaming=False), vid_web_input: gr.Video(visible=True), im_out_row: gr.Row.update(visible=True), im_conv_output: gr.Image(visible=True), im_smooth_output: gr.Image(visible=True), vid_output: gr.Video(visible=False), output_map: gr.Slider(visible=True) } else: if source == "Computer": return { im_tot_row: gr.Row.update(visible=False), vid_tot_row: gr.Row.update(visible=True), im_tot_start: gr.Row.update(visible=False), vid_tot_start: gr.Row.update(visible=True), vid_com_row: gr.Row.update(visible=True), vid_web_row: gr.Row.update(visible=False), im_com_row: gr.Row.update(visible=False), im_web_row: gr.Row.update(visible=False), vid_web_start: gr.Row.update(visible=False), vid_com_start: gr.Row.update(visible=True), im_web_start: gr.Row.update(visible=False), im_com_start: gr.Row.update(visible=False), conv_layer: gr.Slider(visible=False), video_stream: gr.Checkbox(visible=False, value=False), vid_streaming: gr.Image(visible=False, streaming=False), vid_web_input: gr.Video(visible=True), im_out_row: gr.Row.update(visible=False), im_conv_output: gr.Image(visible=True), im_smooth_output: gr.Image(visible=True), vid_output: gr.Video(visible=True), output_map: gr.Slider(visible=False) } else: if is_stream: return { im_tot_row: gr.Row.update(visible=True), vid_tot_row: gr.Row.update(visible=True), im_tot_start: gr.Row.update(visible=False), vid_tot_start: gr.Row.update(visible=True), vid_com_row: gr.Row.update(visible=False), vid_web_row: gr.Row.update(visible=True), im_com_row: gr.Row.update(visible=False), im_web_row: gr.Row.update(visible=False), vid_web_start: gr.Row.update(visible=True), vid_com_start: gr.Row.update(visible=False), im_web_start: gr.Row.update(visible=False), im_com_start: gr.Row.update(visible=False), conv_layer: gr.Slider(visible=False), video_stream: gr.Checkbox(visible=True), vid_streaming: gr.Image(source='webcam', visible=True, streaming=True), vid_web_input: gr.Video(visible=False), im_out_row: gr.Row.update(visible=True), im_conv_output: gr.Image(visible=False), im_smooth_output: gr.Image(visible=False), vid_output: gr.Video(visible=False), output_map: gr.Slider(visible=False) } else: return { im_tot_row: gr.Row.update(visible=False), vid_tot_row: gr.Row.update(visible=True), im_tot_start: gr.Row.update(visible=False), vid_tot_start: gr.Row.update(visible=True), vid_com_row: gr.Row.update(visible=False), vid_web_row: gr.Row.update(visible=True), im_com_row: gr.Row.update(visible=False), im_web_row: gr.Row.update(visible=False), vid_web_start: gr.Row.update(visible=True), vid_com_start: gr.Row.update(visible=False), im_web_start: gr.Row.update(visible=False), im_com_start: gr.Row.update(visible=False), conv_layer: gr.Slider(visible=False), video_stream: gr.Checkbox(visible=True), vid_streaming: gr.Image(visible=False, streaming=False), vid_web_input: gr.Video(visible=True), im_out_row: gr.Row.update(visible=False), im_conv_output: gr.Image(visible=True), im_smooth_output: gr.Image(visible=True), vid_output: gr.Video(visible=True), output_map: gr.Slider(visible=False) } def change_conv_layer(layer): """ Changes the shown convolutional output layer based on gradio slider Args: layer (int): The layer to show Returns: str: The file path of the output image """ return "outputs\\runs\\detect\\exp\\layers\\layer" + str(int(int(layer) - 1)) + '.jpg' def change_output_num(number): return "outputs\\runs\\detect\\exp\\smoothGrad" + str(int(int(number) -1)) + '.jpg' file_type.input(change_file_type, show_progress=True, inputs=[file_type, source_type, video_stream], outputs=[im_tot_row, vid_tot_row, im_tot_start, vid_tot_start, vid_com_row, vid_web_row, im_com_row, im_web_row, vid_web_start, vid_com_start, im_web_start, im_com_start, conv_layer, video_stream, vid_streaming, vid_web_input, im_out_row, im_conv_output, im_smooth_output, vid_output, output_map]) source_type.input(change_file_type, show_progress=True, inputs=[file_type, source_type, video_stream], outputs=[im_tot_row, vid_tot_row, im_tot_start, vid_tot_start, vid_com_row, vid_web_row, im_com_row, im_web_row, vid_web_start, vid_com_start, im_web_start, im_com_start, conv_layer, video_stream, vid_streaming, vid_web_input, im_out_row, im_conv_output, im_smooth_output, vid_output, output_map]) video_stream.input(change_file_type, show_progress=True, inputs=[file_type, source_type, video_stream], outputs=[im_tot_row, vid_tot_row, im_tot_start, vid_tot_start, vid_com_row, vid_web_row, im_com_row, im_web_row, vid_web_start, vid_com_start, im_web_start, im_com_start, conv_layer, video_stream, vid_streaming, vid_web_input, im_out_row, im_conv_output, im_smooth_output, vid_output, output_map]) im_com_but.click(run_image, inputs=[im_com_input, source_type, inf_size, obj_conf_thr, iou_thr, conv_layer, agnostic_nms, output_map, video_stream], outputs=[im_output, im_conv_output, im_smooth_output, labels, formatted_time]) vid_com_but.click(run_video, inputs=[vid_com_input, source_type, inf_size, obj_conf_thr, iou_thr, agnostic_nms, video_stream], outputs=[vid_output]) im_web_but.click(run_image, inputs=[im_web_input, source_type, inf_size, obj_conf_thr, iou_thr, conv_layer, agnostic_nms, output_map, video_stream], outputs=[im_output, im_conv_output, im_smooth_output, labels, formatted_time]) vid_web_but.click(run_video, inputs=[vid_web_input, source_type, inf_size, obj_conf_thr, iou_thr, agnostic_nms, video_stream], outputs=[vid_output]) vid_com_input.upload(correct_video, inputs=[vid_com_input], outputs=[vid_com_input]) vid_web_input.upload(correct_video, inputs=[vid_web_input], outputs=[vid_web_input]) conv_layer.input(change_conv_layer, conv_layer, im_conv_output) vid_streaming.stream(run_stream, inputs=[vid_streaming, source_type, inf_size, obj_conf_thr, iou_thr, conv_layer, agnostic_nms, output_map, video_stream, norm], outputs=[im_output]) output_map.input(change_output_num, output_map, im_smooth_output) demo.load(change_file_type, show_progress=True, inputs=[file_type, source_type, video_stream], outputs=[im_tot_row, vid_tot_row, im_tot_start, vid_tot_start, vid_com_row, vid_web_row, im_com_row, im_web_row, vid_web_start, vid_com_start, im_web_start, im_com_start, conv_layer, video_stream, vid_streaming, vid_web_input, im_out_row, im_conv_output, im_smooth_output, vid_output, output_map] ) if __name__== "__main__" : # If True, it launches Gradio interface # If False, it runs without the interface if True: demo.queue().launch(share=True) else: # run_image("inference\\images\\bus.jpg","Computer",640,0.45,0.25,1,True) run_video("0", "Webcam", 640, 0.25, 0.45, True, True)