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| import gradio as gr | |
| import sys | |
| shared_theme = gr.themes.Base() | |
| 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_train import run_all_files, interface_login | |
| #from train import interface_login, train | |
| def build_train_interface(): | |
| with gr.Blocks(theme=shared_theme) as demo: | |
| gr.Markdown( | |
| """ | |
| # Training Interface for YOLOv7 (Work in progress...) | |
| Train your own YOLOv7 model! | |
| """) | |
| with gr.Row() as file_settings: | |
| # Allows choice for uploading training files or using default official files [official files included in github] | |
| file_type = gr.Radio(label="File Type",info="Choose 'Default' if you are using default values uploaded by server, Choose 'Upload' if you are uploading your own files from your computer", | |
| choices=['Default','Upload'],value='Default',interactive=True,visible=True) | |
| # Allows choice of source and device type | |
| source_type = gr.Radio(label="Source Type",info="'Computer' is set by default", | |
| choices=['Computer'],value='Computer',interactive=True,visible=True) | |
| dev_type = gr.Radio(label="Device Type",info="Choose 'CPU' if you have no gpu, Choose 'Cuda' if you have a cuda enabled gpu", | |
| choices=['CPU','Cuda'],value='CPU',interactive=True,visible=True) | |
| #loggers | |
| with gr.Accordion("Logger Options") as login_accordion: | |
| use_logger = gr.Checkbox(label="Use Logger",info="Check this box if you want to use a logger",visible=True,interactive=True,value=True) | |
| logger_type = gr.Radio(choices=['WANDB', 'ClearML', 'Tensorboard'],value='WANDB',interactive=True,visible=True, | |
| label="Logger",info="Choose which logger to use") | |
| key = gr.Textbox(label="WANDB Key", placeholder="Input your WANDB project key here...", interactive=True) | |
| placeholder = gr.Textbox(label="NULL",placeholder="Not implemented yet, skips loggers process", interactive=False) | |
| response = gr.Textbox(label="NULL",placeholder="Skips loggers process", interactive=False) | |
| login_but = gr.Button(value="Login") | |
| clear_but = gr.ClearButton(value="Clear key", components=[key], | |
| interactive=True,visible=True) | |
| #login_but.click(fn=interface_login,inputs=[logger_type, key],outputs=[]) | |
| #Input parameters | |
| with gr.Row("Inputs") as inputs: | |
| is_finetune = gr.Checkbox(label="Finetune",info="Check this box if you want to finetune a model", interactive=True) | |
| custom_pretrained_file = gr.File(label='Weights File',file_count='single', type='file', visible=True,interactive=True) | |
| pretrained_official = gr.File(label='Official Weight File',type='file',file_count='single',file_types=["pt"],value="weights/yolov7.pt", visible=True,interactive=True) | |
| custom_dataset_file = gr.File(label="Custom Dataset",file_count='single',type='file', | |
| file_types=['.zip'],visible=True,interactive=True) | |
| dataset_official = gr.File(label="Official dataset", type='file',file_count='single',file_types=["zip"], value="coco128.zip", visible=True,interactive=True) | |
| custom_data_file = gr.File(label="Custom Data file",file_count='single',type='file', | |
| file_types=['.yaml'],visible=True,interactive=True) | |
| datafile_official = gr.File(label="Official data file", type='file',file_count='single',file_types=["yaml"], value="yolov7-main/data/coco128.yaml", visible=True,interactive=True) | |
| custom_hyp_file = gr.File(label="Custom hyp file",file_count='single',type='file', | |
| file_types=['.yaml'],visible=True,interactive=True) | |
| hypfile_official = gr.File(label="Official hyp file", type='file',file_count='single',file_types=["yaml"], value="yolov7-main/data/hyp.scratch.p6.yaml", visible=True,interactive=True) | |
| #training settings | |
| with gr.Accordion("""Model settings""") as model_settings: | |
| inf_size = gr.Number(label='Inference Size (pixels)',value=640,precision=0, interactive=True) | |
| pgt_lr = gr.Number(label='Learning rate for plausibility gradient',value=0.02, interactive=True) | |
| pgt_lr_decay = gr.Number(label='decay learning rate for plausibility gradient',value=0.54, interactive=True) | |
| agnostic_nms = gr.Checkbox(label='Agnostic NMS',value=True, interactive=True) | |
| pgt_lr_decay_step = gr.Number(label='Step for decay learning rate',value=1.0, interactive=True) | |
| epochs = gr.Number(label='# of training loops',value=5, interactive=True) | |
| conf_thres = gr.Number(label='object confidence threshold',value=0.45, interactive=True) | |
| batch_size = gr.Number(label='total batch size for GPU',value=10, interactive=True) | |
| #device type settings | |
| with gr.Accordion("Device Options") as device_settings: | |
| device = gr.Radio(choices=['0', '1', '2','3'],value='Cuda',interactive=True,visible=True, | |
| label="Cuda",info="Choose cuda device number") | |
| default_device = gr.Radio(value='CPU',interactive=True,visible=True, | |
| label="CPU",info="defaults to CPU if no cuda device is present") | |
| #run timer | |
| with gr.Row("Timer") as outputs: | |
| formatted_time = gr.Textbox(label = 'Time to Run in Seconds:', value = "") | |
| #output file | |
| with gr.Row("Outputs") as outputs: | |
| output_weight_file = gr.File(type='file',label="Output weight file", | |
| interactive=False,visible=True) | |
| clear_comp_list_1 = [output_weight_file, formatted_time, is_finetune, | |
| custom_pretrained_file, custom_dataset_file, custom_data_file, custom_hyp_file] | |
| clear_comp_list_2 = [output_weight_file, formatted_time, is_finetune, | |
| custom_pretrained_file, pretrained_official, custom_dataset_file, dataset_official, | |
| custom_data_file, datafile_official, custom_hyp_file, hypfile_official] | |
| # Row for start & clear buttons | |
| with gr.Row() as buttons: | |
| start_but = gr.Button(label="Start") | |
| clear_but_1= gr.ClearButton(value='Clear All', components=clear_comp_list_1, | |
| interactive=True,visible=True) | |
| clear_but_2= gr.ClearButton(value='Clear All', components=clear_comp_list_2, | |
| interactive=True,visible=True) | |
| def change_Loggers_type(logger): | |
| """ | |
| Changes the visible components of the gradio interface | |
| Args: | |
| CPU (bool): If default defice is CPU | |
| CUDA (bool): If default device is cuda | |
| Returns: | |
| Dictionary: Each component of the interface that needs to be updated. | |
| """ | |
| if logger == "WANDB": | |
| return {key: gr.Textbox(visible=True), | |
| placeholder: gr.Textbox(visible=False), | |
| response: gr.Textbox(visible=False) | |
| } | |
| elif logger == "ClearML": | |
| return {key: gr.Textbox(visible=False), | |
| placeholder: gr.Textbox(visible=True), | |
| response: gr.Textbox(visible=False) | |
| } | |
| elif logger == "Tensorboard": | |
| return {key: gr.Textbox(visible=False), | |
| placeholder: gr.Textbox(visible=True), | |
| response: gr.Textbox(visible=False) | |
| } | |
| def change_device_type(dev): | |
| """ | |
| Changes the visible components of the gradio interface | |
| Args: | |
| CPU (bool): If default defice is CPU | |
| CUDA (bool): If default device is cuda | |
| Returns: | |
| Dictionary: Each component of the interface that needs to be updated. | |
| """ | |
| if dev == "CPU": | |
| return {default_device: gr.Checkbox(visible=True), | |
| device: gr.Slider(visible=False)} | |
| elif dev == "Cuda": | |
| return {default_device: gr.Checkbox(visible=False), | |
| device: gr.Slider(visible=True)} | |
| def change_file_type(file, source): | |
| """ | |
| Changes the visible components of the gradio interface | |
| Args: | |
| file (str): Type of the file (uploaded or default) | |
| source (str): If the file is uploaded from computer | |
| Returns: | |
| Dictionary: Each component of the interface that needs to be updated. | |
| """ | |
| if file == "Default": | |
| return { | |
| output_weight_file: gr.File(visible=True), | |
| formatted_time: gr.Textbox(visible=True), | |
| is_finetune: gr.File(visible=True), | |
| custom_pretrained_file: gr.File(label='Weights File',file_count='single', type='file',file_types=["pt"], visible=False, | |
| interactive=True), | |
| pretrained_official: gr.Dropdown(visible=True), | |
| custom_dataset_file: gr.File(label="Custom Dataset",file_count='single',type='file', | |
| file_types=['.zip'], visible=False,interactive=True), | |
| dataset_official: gr.Dropdown(visible=True), | |
| custom_data_file: gr.File(label="Custom Data file",file_count='single',type='file', | |
| file_types=['.yaml'], visible=False, interactive=True), | |
| datafile_official: gr.Dropdown(visible=True), | |
| custom_hyp_file: gr.File(label="Custom hyp file",file_count='single',type='file', | |
| file_types=['.yaml'], visible=False, interactive=True), | |
| hypfile_official: gr.Dropdown(visible=True), | |
| formatted_time: gr.Textbox(visible=True), | |
| clear_but_1: gr.ClearButton(visible=True), | |
| clear_but_2: gr.ClearButton(visible=False) | |
| } | |
| elif file == "Upload": | |
| if source == "Computer": | |
| return { | |
| output_weight_file: gr.File(visible=True), | |
| formatted_time: gr.Textbox(visible=True), | |
| is_finetune: gr.File(visible=True), | |
| custom_pretrained_file: gr.File(label='Weights File',file_count='single', type='file',file_types=["pt"], visible=True, | |
| interactive=True), | |
| pretrained_official: gr.Dropdown(visible=False), | |
| custom_dataset_file: gr.File(label="Custom Dataset",file_count='single',type='file', | |
| file_types=['.zip'], visible=True,interactive=True), | |
| dataset_official: gr.Dropdown(visible=False), | |
| custom_data_file: gr.File(label="Custom Data file",file_count='single',type='file', | |
| file_types=['.yaml'], visible=True,interactive=True), | |
| datafile_official: gr.Dropdown(visible=False), | |
| custom_hyp_file: gr.File(label="Custom hyp file",file_count='single',type='file', | |
| file_types=['.yaml'], visible=True,interactive=True), | |
| hypfile_official: gr.Dropdown(visible=False), | |
| formatted_time: gr.Textbox(visible=True), | |
| clear_but_1: gr.ClearButton(visible=False), | |
| clear_but_2: gr.ClearButton(visible=True) | |
| } | |
| change_comp_list = [output_weight_file, formatted_time, is_finetune, | |
| custom_pretrained_file, pretrained_official, custom_dataset_file, dataset_official, clear_but_1, clear_but_2, | |
| custom_data_file, datafile_official, custom_hyp_file, hypfile_official, device, default_device, key, placeholder, response] | |
| # List of gradio components that are input into the run_all method (when start button is clicked) | |
| run_inputs = [pgt_lr, pgt_lr_decay, pgt_lr_decay_step, conf_thres, epochs, conf_thres, | |
| batch_size, default_device, device, inf_size, agnostic_nms, custom_pretrained_file] | |
| # List of gradio components that are output from the run_all method (when start button is clicked) | |
| run_outputs = [output_weight_file, formatted_time] | |
| # 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], outputs=change_comp_list) | |
| source_type.input(change_file_type, show_progress=True, inputs=[file_type, source_type], outputs=change_comp_list) | |
| dev_type.input(change_device_type, show_progress=True, inputs=[dev_type], outputs=change_comp_list) | |
| logger_type.input(change_Loggers_type, show_progress=True, inputs=[logger_type], outputs=change_comp_list) | |
| # When start button is clicked, the run_all method is called | |
| start_but.click(run_all_files, inputs=run_inputs, outputs=run_outputs) | |
| login_but.click(fn=interface_login,inputs=[logger_type, key],outputs=[]) | |
| # When the demo is first started, run the change_file_type method to ensure default settings | |
| demo.load(change_device_type, show_progress=True, inputs=[dev_type], outputs=change_comp_list) | |
| demo.load(change_Loggers_type, show_progress=True, inputs=[logger_type], outputs=change_comp_list) | |
| demo.load(change_file_type, show_progress=True, inputs=[file_type, source_type], outputs=change_comp_list) | |
| return demo | |
| if __name__== "__main__" : | |
| demo = build_train_interface() |