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| import gradio as gr | |
| from frontend.custom_file_reader import File | |
| from backend.InferenceConfig import InferenceConfig, TrackerType | |
| import os | |
| models = { | |
| 'master': 'models/v5m_896_300best.pt', | |
| # 'elwha': 'models/YsEE20.pt', | |
| # 'elwha+kenai_val': 'models/YsEKvE20.pt', | |
| 'elwha': 'models/YsEKtE20.pt', | |
| } | |
| def Upload_Gradio(gradio_components): | |
| with gr.Tabs(): | |
| # Tab - uploading aris files for inference | |
| with gr.Tab("Infer ARIS"): | |
| gr.HTML("<p align='center' style='font-size: large;font-style: italic;'>Submit an .aris file to analyze result.</p>") | |
| default_settings = InferenceConfig() | |
| hyperparams = [] | |
| with gr.Accordion("Advanced Settings", open=False): | |
| default_model = default_settings.find_model(models) | |
| hyperparams.append(gr.Dropdown(label="Model", value=default_model, choices=list(models.keys()))) | |
| gr.Markdown("Detection Parameters") | |
| with gr.Row(): | |
| hyperparams.append(gr.Slider(0, 1, value=default_settings.conf_thresh, label="Confidence Threshold", info="Confidence cutoff for detection boxes")) | |
| hyperparams.append(gr.Slider(0, 1, value=default_settings.nms_iou, label="NMS IoU", info="IoU threshold for non-max suppression")) | |
| gr.Markdown("Tracking Parameters") | |
| with gr.Row(): | |
| hyperparams.append(gr.Slider(0, 100, value=default_settings.min_hits, label="Min Hits", info="Minimum number of frames a fish has to appear in to count")) | |
| hyperparams.append(gr.Slider(0, 100, value=default_settings.max_age, label="Max Age", info="Max age of occlusion before track is split")) | |
| default_tracker = TrackerType.toString(default_settings.associative_tracker) | |
| tracker = gr.Dropdown(["None", "Confidence Boost", "ByteTrack"], value=default_tracker, label="Associative Tracking") | |
| hyperparams.append(tracker) | |
| with gr.Row(visible=default_tracker=="Confidence Boost") as track_row: | |
| hyperparams.append(gr.Slider(0, 5, value=default_settings.boost_power, label="Boost Power", info="Scalar multiplier for the boost amount")) | |
| hyperparams.append(gr.Slider(0, 1, value=default_settings.boost_decay, label="Boost Decay", info="Exponential decay parameter for boost based on frame time difference")) | |
| tracker.change(lambda x: gr.update(visible=(x=="Confidence Boost")), tracker, track_row) | |
| with gr.Row(visible=default_tracker=="ByteTrack") as track_row: | |
| hyperparams.append(gr.Slider(0, 1, value=default_settings.byte_low_conf, label="Low Conf Threshold", info="Confidence threshold for the low detection group")) | |
| hyperparams.append(gr.Slider(0, 1, value=default_settings.byte_high_conf, label="High Conf Threshold", info="Confidence threshold for the high detection group")) | |
| tracker.change(lambda x: gr.update(visible=(x=="ByteTrack")), tracker, track_row) | |
| gr.Markdown("Other") | |
| with gr.Row(): | |
| hyperparams.append(gr.Slider(0, 3, value=default_settings.min_length, label="Min Length", info="Minimum length of fish (meters) in order for it to count")) | |
| hyperparams.append(gr.Slider(0, 3, value=default_settings.max_length, label="Max Length", info="Maximum length of fish (meters) in order for it to count. (disable at 0)")) | |
| hyperparams.append(gr.Slider(0, 10, value=default_settings.min_travel, label="Min Travel", info="Minimum travel distance of track (meters) in order for it to count")) | |
| gradio_components['hyperparams'] = hyperparams | |
| with gr.Row(): | |
| hyperparams.append(gr.CheckboxGroup([("Generate Annotated Video"), ("Generate Manual Marking"), ("Generate PDF"), ("Automatically download result")], label="Output settings", interactive=True, value=["Generate Annotated Video"])) | |
| #Input field for aris submission | |
| gradio_components['input'] = File(file_types=[".aris", ".ddf"], type="binary", label="ARIS Input", file_count="multiple") | |
| example_name = "static/example.aris" | |
| gradio_components['examples'] = gr.Examples(examples=[[example_name]], inputs=gradio_components['input']) | |
| gradio_components['inference_btn'] = gr.Button("Run") | |
| # Tab - uploading old result files to review | |
| with gr.Tab("Open Result"): | |
| gr.HTML(""" | |
| <p align='center' style='font-size: large;font-style: italic;'>Submit an old zip file of results to visualize.</p> | |
| <p align='center' style='font-size: large;font-style: italic;'>If you want to edit annotations, also submit an aris file.</p> | |
| """) | |
| # Input for .zip result file | |
| gradio_components['result_input'] = File(file_types=[".zip"], type="binary", label="Upload result file", file_count="multiple") | |
| # Optional input for aris file to help with annotation editing | |
| gradio_components['result_aris_input'] = File(file_types=[".aris", ".ddf"], type="binary", label="Upload aris file (optional)", file_count="multiple") | |
| # Button for initializing review | |
| gradio_components['open_result_btn'] = gr.Button("View Result") | |