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| import sys # System package for path dependencies | |
| sys.path.append('Engineering-Clinic-Emerging-AI-Design-Interface/Interface_Dependencies') | |
| sys.path.append('Engineering-Clinic-Emerging-AI-Design-Interface/Interface') | |
| sys.path.append('Engineering-Clinic-Emerging-AI-Design-Interface/yolov7-main') | |
| sys.path.append('Engineering-Clinic-Emerging-AI-Design-Interface') | |
| sys.path.append('Interface_Dependencies') | |
| sys.path.append('Interface') | |
| from run_methods import run_all, correct_video | |
| import gradio as gr # Gradio package for interface | |
| # Gradio Interface Code | |
| def build_detect_interface(): | |
| with gr.Blocks(title="yolov7 Interface",theme=gr.themes.Base()) as demo: | |
| gr.Markdown( | |
| """ | |
| # Image & Video Interface for yolov7 Model | |
| ### Upload your own image or video and watch yolov7 try to guess what it is! | |
| """) | |
| # Row for for input & output settings | |
| with gr.Row() as file_settings: | |
| # Allows the user to toggle between the advanced and simple interfaces | |
| skill_type = gr.Radio(label="Skill Type",info="Choose 'Advanced' if you would like to use the advanced interface, Choose 'Simple' if you would like that version", | |
| choices=['Advanced','Simple', 'Help'],value='Simple',show_label=True,interactive=True,visible=True) | |
| # 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,visible=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,visible=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 webcam 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) | |
| # Row for all inputs & outputs | |
| with gr.Row() as inputs_outputs: | |
| # Default input image: Visible, Upload from computer | |
| input_im = gr.Image(source="upload",type='filepath',label="Input Image", | |
| show_download_button=True,show_share_button=True,interactive=True,visible=False) | |
| # Default Boxed output image: Visible | |
| output_box_im = gr.Image(type='filepath',label="Output Image", | |
| show_download_button=True,show_share_button=True,interactive=False,visible=False) | |
| # Defualt Convolutional output image: Visible | |
| output_conv_im = gr.Image(type='filepath',label="Output Convolution", | |
| show_download_button=True,show_share_button=True,interactive=False,visible=False) | |
| # Default Gradient output image: Visible | |
| output_grad_im = gr.Image(type='filepath',label="Output Smooth Gradient", | |
| show_download_button=True,show_share_button=True,interactive=False,visible=False) | |
| # Default label output textbox: Visible | |
| labels = gr.Textbox(label='Top Predictions:', value = "") | |
| # Default plaus output textbox: Visible | |
| plaus = gr.Textbox(label = "Plausibility Score:", value="") | |
| # Default time output textbox: Visible | |
| formatted_time = gr.Textbox(label = 'Total and Detection Time in Seconds:', value = "",scale=6) | |
| # Default input video: Not visible, Upload from computer | |
| input_vid = gr.Video(source="upload",label="Input Video", | |
| show_share_button=True,interactive=True,visible=False) | |
| # Default Boxed output video: Not visible | |
| output_box_vid = gr.Video(label="Output Video",show_share_button=True,visible=False) | |
| #An option to bring up a help menu | |
| help_box = gr.Textbox(lines=5, label="Help Box", visible=False) | |
| # List of components for clearing | |
| clear_comp_list = [input_im, output_box_im, output_conv_im, output_grad_im, labels, plaus, formatted_time, input_vid, output_box_vid] | |
| # Row for start, clear and demo buttons | |
| with gr.Row() as buttons: | |
| start_but = gr.Button(value="Start") | |
| demo1_but = gr.Button(value="ImageDemo") | |
| demo2_but = gr.Button(value="VideoDemo") | |
| clear_but = gr.ClearButton(value='Clear All',components=clear_comp_list, | |
| interactive=True,visible=True) | |
| # Row for model settings | |
| with gr.Row() as model_settings: | |
| # Pixel size of the inference [Possibly useless, may remove] | |
| inf_size = gr.Number(label='Inference Size (pixels)',value=640,precision=0,visible=False) | |
| # Object confidence threshold | |
| obj_conf_thr = gr.Number(label='Object Confidence Threshold',value=0.25,visible=False) | |
| # Intersection of union threshold | |
| iou_thr = gr.Number(label='IOU threshold for NMS',value=0.45,visible=False) | |
| # Agnostic NMS boolean | |
| agnostic_nms = gr.Checkbox(label='Agnostic NMS',value=True, visible=False) | |
| # Normailze gradient boolean | |
| norm = gr.Checkbox(label='Normalize Gradient',value=False,visible=False) | |
| # Weights File Upload | |
| weights = gr.File(label='Weights File',type='file',file_count='single',file_types=["pt"],value="weights/yolov7.pt",visible=False) | |
| #Consider making this its own file | |
| def change_file_type(file, source, is_stream, skill_type): | |
| """ | |
| 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 | |
| is_stream (bool): If the video is streaming or uploaded | |
| Returns: | |
| Dictionary: Each component of the interface that needs to be updated. | |
| """ | |
| help_string = ("Variables within the interface: \n \ | |
| Simple Mode: \n \ | |
| Skill Type - The mode the interface will be set to. Simple is recommended for new users! \n \ | |
| File Type - Set the interface for image or video input \n \ | |
| Source Type - Set the input for media to computer(will allow uploads) or webcam(will use your devices webcam) \n \ | |
| stream from webcam? - Toggle the ability to livestream video from webcam \n \ | |
| Start - Run the interface with the set parameters and media \n \ | |
| ImageDemo - Run a demo to test the interface with a stock image \n \ | |
| VideoDemo - Run a demo to test the interface with a stock video \n \ | |
| ClearAll - Clear all of the input/output figures on the interface \n \ | |
| Advanced Mode: \n \ | |
| Convolution Layer - The convolutional layor extracted from the neural network. There are 17 of these to scroll between. \n \ | |
| Map Output Number - The attribution map. 1 is bounding box, 2 is object, and 3 is class. Currently, this is from the model not loss. \n \ | |
| Top Predictions - A list of the predictions along with their confidence percentage \n \ | |
| Plausibility Score - The measurement of how much the predicted bounding boxes overlap with the attributions generated (bounding box model output) \n \ | |
| Inference Size - The resolution of the image that will be interpreted (default is 640 by 640 pixels) \n \ | |
| Object Confidence Threshold - The minimum confidence required to display a bounding box \n \ | |
| IOU Threshold for NMS - The minimum confidence required for a bounding box to surpass another in cases of multiple predictions \n \ | |
| Agnostic NMS - Enable non max suppression to use the bounding boxes with the highest confidence in prediction \n \ | |
| Normalize Gradient - Scale the gradient vector to have a magnitude of 1 \n \ | |
| Weights File - A .pt file that contains the weight values that make the filter. This contains the classes and will greatly affect how an image or video is classified") | |
| if file == "Image": | |
| if source == "Computer": | |
| if skill_type == "Advanced": | |
| return { | |
| conv_layer: gr.Slider(visible=True), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=True), | |
| input_im: gr.Image(source="upload",type='filepath',label="Input Image", | |
| show_download_button=True,show_share_button=True,interactive=True,visible=True,streaming=False,scale=3), | |
| output_box_im: gr.Image(visible=True,scale=3), | |
| output_conv_im: gr.Image(visible=True,scale=3), | |
| output_grad_im: gr.Image(visible=True,scale=3), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=True), | |
| labels: gr.Textbox(visible=True,scale=1), | |
| plaus: gr.Textbox(visible=True,scale=1), | |
| formatted_time: gr.Textbox(visible=True,scale=1), | |
| help_box: gr.Textbox(visible=False, value=help_string), | |
| inf_size: gr.Number(visible=True), | |
| obj_conf_thr: gr.Number(visible=True), | |
| iou_thr: gr.Number(visible=True), | |
| agnostic_nms: gr.Checkbox(visible=True), | |
| weights: gr.File(visible=True) | |
| } | |
| elif skill_type == "Simple": | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(source="upload",type='filepath',label="Input Image", | |
| show_download_button=True,show_share_button=True,interactive=True,visible=True,streaming=False,scale=3), | |
| output_box_im: gr.Image(visible=True,scale=3), | |
| output_conv_im: gr.Image(visible=False,scale=3), | |
| output_grad_im: gr.Image(visible=False,scale=3), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=False), | |
| labels: gr.Textbox(visible=False,scale=1), | |
| plaus: gr.Textbox(visible=False,scale=1), | |
| formatted_time: gr.Textbox(visible=False,scale=1), | |
| help_box: gr.Textbox(visible=False, value=help_string), | |
| inf_size: gr.Number(visible=False), | |
| obj_conf_thr: gr.Number(visible=False), | |
| iou_thr: gr.Number(visible=False), | |
| agnostic_nms: gr.Checkbox(visible=False), | |
| weights: gr.File(visible=False) | |
| } | |
| # Else its help | |
| else: | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(source="upload",type='filepath',label="Input Image", | |
| show_download_button=True,show_share_button=True,interactive=True,visible=False,streaming=False,scale=3), | |
| output_box_im: gr.Image(visible=False,scale=3), | |
| output_conv_im: gr.Image(visible=False,scale=3), | |
| output_grad_im: gr.Image(visible=False,scale=3), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=False), | |
| labels: gr.Textbox(visible=False,scale=1), | |
| plaus: gr.Textbox(visible=False,scale=1), | |
| formatted_time: gr.Textbox(visible=False,scale=1), | |
| help_box: gr.Textbox(visible=True, value=help_string,scale=10), | |
| inf_size: gr.Number(visible=False), | |
| obj_conf_thr: gr.Number(visible=False), | |
| iou_thr: gr.Number(visible=False), | |
| agnostic_nms: gr.Checkbox(visible=False), | |
| weights: gr.File(visible=False) | |
| } | |
| elif source == "Webcam": | |
| if skill_type == "Advanced": | |
| return { | |
| conv_layer: gr.Slider(visible=True), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=True), | |
| input_im: gr.Image(type='pil',source="webcam",label="Input Image", | |
| visible=True,interactive=True,streaming=False,scale=3), | |
| output_box_im: gr.Image(visible=True,scale=3), | |
| output_conv_im: gr.Image(visible=True,scale=3), | |
| output_grad_im: gr.Image(visible=True,scale=3), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=True), | |
| labels: gr.Textbox(visible=True), | |
| plaus: gr.Textbox(visible=True), | |
| formatted_time: gr.Textbox(visible=True), | |
| help_box: gr.Textbox(visible=False, value=help_string), | |
| inf_size: gr.Number(visible=True), | |
| obj_conf_thr: gr.Number(visible=True), | |
| iou_thr: gr.Number(visible=True), | |
| agnostic_nms: gr.Checkbox(visible=True), | |
| weights: gr.File(visible=True) | |
| } | |
| elif skill_type == "Simple": | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(type='pil',source="webcam",label="Input Image", | |
| visible=True,interactive=True,streaming=False,scale=3), | |
| output_box_im: gr.Image(visible=True,scale=3), | |
| output_conv_im: gr.Image(visible=False,scale=3), | |
| output_grad_im: gr.Image(visible=False,scale=3), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=False), | |
| labels: gr.Textbox(visible=False), | |
| plaus: gr.Textbox(visible=False), | |
| formatted_time: gr.Textbox(visible=False), | |
| help_box: gr.Textbox(visible=False, value=help_string), | |
| inf_size: gr.Number(visible=False), | |
| obj_conf_thr: gr.Number(visible=False), | |
| iou_thr: gr.Number(visible=False), | |
| agnostic_nms: gr.Checkbox(visible=False), | |
| weights: gr.File(visible=False) | |
| } | |
| else: | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(source="upload",type='filepath',label="Input Image", | |
| show_download_button=True,show_share_button=True,interactive=True,visible=False,streaming=False,scale=3), | |
| output_box_im: gr.Image(visible=False,scale=3), | |
| output_conv_im: gr.Image(visible=False,scale=3), | |
| output_grad_im: gr.Image(visible=False,scale=3), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=False), | |
| labels: gr.Textbox(visible=False,scale=1), | |
| plaus: gr.Textbox(visible=False,scale=1), | |
| formatted_time: gr.Textbox(visible=False,scale=1), | |
| help_box: gr.Textbox(visible=True, value=help_string,scale=10), | |
| inf_size: gr.Number(visible=False), | |
| obj_conf_thr: gr.Number(visible=False), | |
| iou_thr: gr.Number(visible=False), | |
| agnostic_nms: gr.Checkbox(visible=False), | |
| weights: gr.File(visible=False) | |
| } | |
| elif file == "Video": | |
| if source == "Computer": | |
| if skill_type == "Advanced": | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(visible=False,streaming=False), | |
| output_box_im: gr.Image(visible=False), | |
| output_conv_im: gr.Image(visible=False), | |
| output_grad_im: gr.Image(visible=False), | |
| input_vid: gr.Video(source="upload",label="Input Video", | |
| show_share_button=True,interactive=True,visible=True,scale=6), | |
| output_box_vid: gr.Video(label="Output Video",show_share_button=True,visible=True,scale=6), | |
| norm: gr.Checkbox(visible=True), | |
| labels: gr.Textbox(visible=False), | |
| plaus: gr.Textbox(visible=False), | |
| formatted_time: gr.Textbox(visible=True,scale=1), | |
| help_box: gr.Textbox(visible=False, value=help_string,scale=10), | |
| inf_size: gr.Number(visible=True), | |
| obj_conf_thr: gr.Number(visible=True), | |
| iou_thr: gr.Number(visible=True), | |
| agnostic_nms: gr.Checkbox(visible=True), | |
| weights: gr.File(visible=True) | |
| } | |
| elif skill_type == "Simple": | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(visible=False,streaming=False), | |
| output_box_im: gr.Image(visible=False), | |
| output_conv_im: gr.Image(visible=False), | |
| output_grad_im: gr.Image(visible=False), | |
| input_vid: gr.Video(source="upload",label="Input Video", | |
| show_share_button=True,interactive=True,visible=True,scale=6), | |
| output_box_vid: gr.Video(label="Output Video",show_share_button=True,visible=True,scale=6), | |
| norm: gr.Checkbox(visible=False), | |
| labels: gr.Textbox(visible=False), | |
| plaus: gr.Textbox(visible=False), | |
| formatted_time: gr.Textbox(visible=False), | |
| help_box: gr.Textbox(visible=False, value=help_string), | |
| inf_size: gr.Number(visible=False), | |
| obj_conf_thr: gr.Number(visible=False), | |
| iou_thr: gr.Number(visible=False), | |
| agnostic_nms: gr.Checkbox(visible=False), | |
| weights: gr.File(visible=False) | |
| } | |
| else: | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(source="upload",type='filepath',label="Input Image", | |
| show_download_button=True,show_share_button=True,interactive=True,visible=False,streaming=False,scale=3), | |
| output_box_im: gr.Image(visible=False,scale=3), | |
| output_conv_im: gr.Image(visible=False,scale=3), | |
| output_grad_im: gr.Image(visible=False,scale=3), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=False), | |
| labels: gr.Textbox(visible=False,scale=1), | |
| plaus: gr.Textbox(visible=False,scale=1), | |
| formatted_time: gr.Textbox(visible=False,scale=1), | |
| help_box: gr.Textbox(visible=True, value=help_string,scale=10), | |
| inf_size: gr.Number(visible=False), | |
| obj_conf_thr: gr.Number(visible=False), | |
| iou_thr: gr.Number(visible=False), | |
| agnostic_nms: gr.Checkbox(visible=False), | |
| weights: gr.File(visible=False) | |
| } | |
| #TODO-clinic: Fix possible streaming issues | |
| elif source == "Webcam": | |
| if is_stream: | |
| if skill_type == "Advanced": | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=True), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(type='pil',source="webcam",label="Input Image", | |
| streaming=True,visible=True,interactive=True,scale=6), | |
| output_box_im: gr.Image(visible=True,scale=6), | |
| output_conv_im: gr.Image(visible=False), #TODO-clinic: We may not want to hide all of these | |
| output_grad_im: gr.Image(visible=False), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=True), | |
| labels: gr.Textbox(visible=False), | |
| plaus: gr.Textbox(visible=False), | |
| formatted_time: gr.Textbox(visible=True,scale=1), | |
| help_box: gr.Textbox(visible=False, value=help_string), | |
| inf_size: gr.Number(visible=True), | |
| obj_conf_thr: gr.Number(visible=True), | |
| iou_thr: gr.Number(visible=True), | |
| agnostic_nms: gr.Checkbox(visible=True), | |
| weights: gr.File(visible=True) | |
| } | |
| elif skill_type == "Simple": | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=True), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(type='pil',source="webcam",label="Input Image", | |
| streaming=True,visible=True,interactive=True,scale=6), | |
| output_box_im: gr.Image(visible=True,scale=6), | |
| output_conv_im: gr.Image(visible=False), | |
| output_grad_im: gr.Image(visible=False), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=False), | |
| labels: gr.Textbox(visible=False), | |
| plaus: gr.Textbox(visible=False), | |
| formatted_time: gr.Textbox(visible=False), | |
| help_box: gr.Textbox(visible=False, value=help_string), | |
| inf_size: gr.Number(visible=False), | |
| obj_conf_thr: gr.Number(visible=False), | |
| iou_thr: gr.Number(visible=False), | |
| agnostic_nms: gr.Checkbox(visible=False), | |
| weights: gr.File(visible=False) | |
| } | |
| else: | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(source="upload",type='filepath',label="Input Image", | |
| show_download_button=True,show_share_button=True,interactive=True,visible=False,streaming=False,scale=3), | |
| output_box_im: gr.Image(visible=False,scale=3), | |
| output_conv_im: gr.Image(visible=False,scale=3), | |
| output_grad_im: gr.Image(visible=False,scale=3), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=False), | |
| labels: gr.Textbox(visible=False,scale=1), | |
| plaus: gr.Textbox(visible=False,scale=1), | |
| formatted_time: gr.Textbox(visible=False,scale=1), | |
| help_box: gr.Textbox(visible=True, value=help_string,scale=10), | |
| inf_size: gr.Number(visible=False), | |
| obj_conf_thr: gr.Number(visible=False), | |
| iou_thr: gr.Number(visible=False), | |
| agnostic_nms: gr.Checkbox(visible=False), | |
| weights: gr.File(visible=False) | |
| } | |
| elif not is_stream: | |
| if skill_type == "Advanced": | |
| return { | |
| #TODO-clinic: We may not want to hide all of these | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=True, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(visible=False,streaming=False), | |
| output_box_im: gr.Image(visible=False), | |
| output_conv_im: gr.Image(visible=False), | |
| output_grad_im: gr.Image(visible=False), | |
| input_vid: gr.Video(label="Input Video",source="webcam", | |
| show_share_button=True,interactive=True,visible=True,scale=6), | |
| output_box_vid: gr.Video(label="Output Video",show_share_button=True,visible=True,scale=6), | |
| norm: gr.Checkbox(visible=True), | |
| labels: gr.Textbox(visible=False), | |
| plaus: gr.Textbox(visible=False), | |
| formatted_time: gr.Textbox(visible=True,scale=1), | |
| help_box: gr.Textbox(visible=False, value=help_string), | |
| inf_size: gr.Number(visible=True), | |
| obj_conf_thr: gr.Number(visible=True), | |
| iou_thr: gr.Number(visible=True), | |
| agnostic_nms: gr.Checkbox(visible=True), | |
| weights: gr.File(visible=True) | |
| } | |
| elif skill_type == "Simple": | |
| #TODO-clinic: Update for simple | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=True, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(visible=False,streaming=False), | |
| output_box_im: gr.Image(visible=False), | |
| output_conv_im: gr.Image(visible=False), | |
| output_grad_im: gr.Image(visible=False), | |
| input_vid: gr.Video(label="Input Video",source="webcam", | |
| show_share_button=True,interactive=True,visible=True,scale=6), | |
| output_box_vid: gr.Video(label="Output Video",show_share_button=True,visible=True,scale=6), | |
| norm: gr.Checkbox(visible=False), | |
| labels: gr.Textbox(visible=False), | |
| plaus: gr.Textbox(visible=False), | |
| formatted_time: gr.Textbox(visible=False), | |
| help_box: gr.Textbox(visible=False, value=help_string), | |
| inf_size: gr.Number(visible=False), | |
| obj_conf_thr: gr.Number(visible=False), | |
| iou_thr: gr.Number(visible=False), | |
| agnostic_nms: gr.Checkbox(visible=False), | |
| weights: gr.File(visible=False) | |
| } | |
| else: | |
| return { | |
| conv_layer: gr.Slider(visible=False), | |
| video_stream: gr.Checkbox(visible=False, value=False), | |
| output_map: gr.Slider(visible=False), | |
| input_im: gr.Image(source="upload",type='filepath',label="Input Image", | |
| show_download_button=True,show_share_button=True,interactive=True,visible=False,streaming=False,scale=3), | |
| output_box_im: gr.Image(visible=False,scale=3), | |
| output_conv_im: gr.Image(visible=False,scale=3), | |
| output_grad_im: gr.Image(visible=False,scale=3), | |
| input_vid: gr.Video(visible=False), | |
| output_box_vid: gr.Video(visible=False), | |
| norm: gr.Checkbox(visible=False), | |
| labels: gr.Textbox(visible=False,scale=1), | |
| plaus: gr.Textbox(visible=False,scale=1), | |
| formatted_time: gr.Textbox(visible=False,scale=1), | |
| help_box: gr.Textbox(visible=True, value=help_string,scale=10), | |
| inf_size: gr.Number(visible=False), | |
| obj_conf_thr: gr.Number(visible=False), | |
| iou_thr: gr.Number(visible=False), | |
| agnostic_nms: gr.Checkbox(visible=False), | |
| weights: gr.File(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): | |
| """ | |
| Changes the shown gradient map based on gradio slider | |
| Args: | |
| number (int): The gradient map to show | |
| Returns: | |
| str: The file path of the output image | |
| """ | |
| return "outputs/runs/detect/exp/smoothGrad" + str(int(int(number) -1)) + '.jpg' | |
| def demo1(): | |
| """ | |
| Run a test image file as a demo | |
| """ | |
| #TODO-clinic - There may be a better way to do this (move to another file) | |
| 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,visible=False) | |
| input_im = gr.Image(type='filepath',label="Input Image",value= "references/inference/images/bus.jpg", | |
| show_download_button=True,show_share_button=True,interactive=True,visible=False) | |
| input_vid = gr.Video(source="upload",label="Input Video", | |
| show_share_button=True,interactive=True,visible=False) | |
| 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,visible=False) | |
| inf_size = gr.Number(label='Inference Size (pixels)',value=640,precision=0,visible=False) | |
| obj_conf_thr = gr.Number(label='Object Confidence Threshold',value=0.25,visible=False) | |
| iou_thr = gr.Number(label='IOU threshold for NMS',value=0.45,visible=False) | |
| 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,visible=False) | |
| agnostic_nms = gr.Checkbox(label='Agnostic NMS',value=True,visible=False) | |
| 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,visible=False) | |
| 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) | |
| norm = gr.Checkbox(label='Normalize Gradient',value=False,visible=False) | |
| weights = gr.File(label='Weights File',type='file',file_count='single',file_types=["pt"],value="weights/yolov7.pt",visible=False) | |
| skill_type = gr.Radio(label="Skill Type",info="Choose 'Advanced' if you would like to use the advanced interface, 'Simple' if you would like that version, or help for more info", | |
| choices=['Advanced','Simple'],value='Advanced',show_label=True,interactive=True,visible=False) | |
| demo1_inputs = [file_type, input_im, input_vid, source_type, | |
| inf_size, obj_conf_thr, iou_thr, conv_layer, | |
| agnostic_nms, output_map, video_stream, norm, weights,skill_type] | |
| return demo1_inputs | |
| def demo2(): | |
| """ | |
| Run a test video file as a demo | |
| """ | |
| #TODO-clinic - There may be a better way to do this (move to another file) | |
| 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='Video',show_label=True,interactive=True,visible=False) | |
| input_im = gr.Image(type='filepath',label="Input Image", | |
| show_download_button=True,show_share_button=True,interactive=True,visible=False) | |
| input_vid = gr.Video(source="upload",label="Input Video", | |
| show_share_button=True,interactive=True,visible=False,value= "references/inference/videos/ducks.mp4") | |
| 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,visible=False) | |
| inf_size = gr.Number(label='Inference Size (pixels)',value=640,precision=0,visible=False) | |
| obj_conf_thr = gr.Number(label='Object Confidence Threshold',value=0.25,visible=False) | |
| iou_thr = gr.Number(label='IOU threshold for NMS',value=0.45,visible=False) | |
| 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,visible=False) | |
| agnostic_nms = gr.Checkbox(label='Agnostic NMS',value=True,visible=False) | |
| 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,visible=False) | |
| 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) | |
| norm = gr.Checkbox(label='Normalize Gradient',value=False,visible=False) | |
| weights = gr.File(label='Weights File',type='file',file_count='single',file_types=["pt"],value="weights/yolov7.pt",visible=False) | |
| skill_type = gr.Radio(label="Skill Type",info="Choose 'Advanced' if you would like to use the advanced interface, Choose 'Simple' if you would like that version", | |
| choices=['Advanced','Simple'],value='Advanced',show_label=True,interactive=True,visible=False) | |
| demo2_inputs = [file_type, input_im, input_vid, source_type, | |
| inf_size, obj_conf_thr, iou_thr, conv_layer, | |
| agnostic_nms, output_map, video_stream, norm, weights,skill_type] | |
| return demo2_inputs | |
| # List of gradio components that change during method "change_file_type" | |
| change_comp_list = [conv_layer, video_stream, output_map, | |
| input_im, output_box_im, output_conv_im, output_grad_im, | |
| input_vid, output_box_vid, norm, labels, plaus, formatted_time, | |
| help_box, inf_size, obj_conf_thr, iou_thr, agnostic_nms, weights] | |
| # List of gradio components that are input into the run_all method (when start button is clicked) | |
| run_inputs = [file_type, input_im, input_vid, source_type, | |
| inf_size, obj_conf_thr, iou_thr, conv_layer, | |
| agnostic_nms, output_map, video_stream, norm, weights, skill_type] #TODO-clinic: Skill_type might be able to be removed here | |
| # List of gradio components that are output from the run_all method (when start button is clicked) | |
| run_outputs = [output_box_im, output_conv_im, output_grad_im, labels, plaus, formatted_time, output_box_vid, input_im, input_vid] | |
| # When these settings are changed, the change_file_type method is called | |
| file_type.input(change_file_type, show_progress=True, inputs=[file_type, source_type, video_stream, skill_type], outputs=change_comp_list) | |
| source_type.input(change_file_type, show_progress=True, inputs=[file_type, source_type, video_stream, skill_type], outputs=change_comp_list) | |
| video_stream.input(change_file_type, show_progress=True, inputs=[file_type, source_type, video_stream, skill_type], outputs=change_comp_list) | |
| skill_type.input(change_file_type, show_progress=True, inputs=[file_type, source_type, video_stream, skill_type], outputs=change_comp_list) | |
| # When start button is clicked, the run_all method is called | |
| start_but.click(run_all, inputs=run_inputs, outputs=run_outputs) | |
| # When demo1 button is clicked, run the function with stored params | |
| demo1_but.click(run_all, inputs=demo1(), outputs=run_outputs) | |
| # # When demo2 button is clicked, run the function with stored params | |
| demo2_but.click(run_all, inputs=demo2(), outputs=run_outputs) | |
| # When video is uploaded, the correct_video method is called | |
| input_vid.upload(correct_video, inputs=[input_vid], outputs=[input_vid]) | |
| # When the convolutional layer setting is changed, the change_conv_layer method is called | |
| conv_layer.input(change_conv_layer, conv_layer, output_conv_im) | |
| # When the stream setting is true, run the stream | |
| input_im.stream(run_all, inputs=run_inputs, outputs=run_outputs) | |
| # When the gradient number is changed, the change_output_num method is called | |
| output_map.input(change_output_num, output_map, output_grad_im) | |
| # When the demo is first started, run the change_file_type method to ensure default settings | |
| demo.load(change_file_type, show_progress=True, inputs=[file_type, source_type, video_stream, skill_type], outputs=change_comp_list) | |
| return demo | |
| # #Used for debugging | |
| # if __name__== "__main__" : | |
| # # If True, it launches Gradio interface | |
| # # If False, it runs without the interface (for better debugging) | |
| # if True: | |
| # # demo.queue().launch(share=True) | |
| # demo.queue().launch() | |
| # else: | |
| # #Test with yolo (weights and normal photo) | |
| # run_all('Image','references\\inference\\images\\bus.jpg', 'None', 'Computer', 640,0.25,0.45,1,True,1,False,False,"yolov7.pt", "Advanced") | |
| # #Test drone (weights and drone photo) TODO: Weight set may not be included in the repo | |
| # #run_all('Image','references\\inference\\images\\V_DRONE_113_34.jpg', 'None', 'Computer', 640,0.25,0.45,1,True,1,False,False,"drone_63.pt", "Advanced") |