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| import gradio as gr | |
| from tifffile import imread | |
| from PIL import Image | |
| from path_analysis.analyse import analyse_paths | |
| import numpy as np | |
| # Function to preview the imported image | |
| def preview_image(file1): | |
| if file1: | |
| print('Uploading image', file1.name) | |
| im = imread(file1.name) | |
| print(im.ndim, im.shape) | |
| if im.ndim>2: | |
| return Image.fromarray(np.max(im, axis=0)) | |
| else: | |
| return Image.fromarray(im) | |
| else: | |
| return None | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| # Inputs for cell ID, image, and path | |
| cellid_input = gr.Textbox(label="Cell ID", placeholder="Image_1") | |
| image_input = gr.File(label="Input foci image") | |
| image_preview = gr.Image(label="Max projection of foci image") | |
| image_input.change(fn=preview_image, inputs=image_input, outputs=image_preview) | |
| path_input = gr.File(label="SNT traces file") | |
| # Additional options wrapped in an accordion for better UI experience | |
| with gr.Accordion("Additional options ..."): | |
| sphere_radius = gr.Number(label="Trace sphere radius (um)", value=0.1984125, interactive=True) | |
| peak_threshold = gr.Number(label="Peak relative threshold", value=0.4, interactive=True) | |
| # Resolutions for xy and z axis | |
| with gr.Row(): | |
| xy_res = gr.Number(label='xy-yesolution (um)', value=0.0396825, interactive=True) | |
| z_res = gr.Number(label='z resolution (um)', value=0.0909184, interactive=True) | |
| # Resolutions for xy and z axis | |
| threshold_type = gr.Radio(["per-trace", "per-cell"], label="Threshold-type", value="per-trace", interactive=True) | |
| use_corrected_positions = gr.Checkbox(label="Correct foci position measurements", value=True, interactive=True) | |
| screening_distance = gr.Number(label='Screening distance (voxels)', value=10, interactive=True) | |
| # The output column showing the result of processing | |
| with gr.Column(): | |
| trace_output = gr.Image(label="Overlayed paths") | |
| image_output=gr.Gallery(label="Traced paths") | |
| plot_output=gr.Plot(label="Foci intensity traces") | |
| data_output=gr.DataFrame(label="Detected peak data")#, "Peak 1 pos", "Peak 1 int"]) | |
| data_file_output=gr.File(label="Output data file (.csv)") | |
| def process(cellid_input, image_input, path_input, sphere_radius, peak_threshold, xy_res, z_res, threshold_type, use_corrected_positions, screening_distance): | |
| config = { 'sphere_radius': sphere_radius, | |
| 'peak_threshold': peak_threshold, | |
| 'xy_res': xy_res, | |
| 'z_res': z_res, | |
| 'threshold_type': threshold_type, | |
| 'use_corrected_positions': use_corrected_positions, | |
| 'screening_distance': screening_distance, | |
| } | |
| paths, traces, fig, extracted_peaks = analyse_paths(cellid_input, image_input.name, path_input.name, config) | |
| extracted_peaks.to_csv('output.csv') | |
| print('extracted', extracted_peaks) | |
| return paths, [Image.fromarray(im) for im in traces], fig, extracted_peaks, 'output.csv' | |
| with gr.Row(): | |
| greet_btn = gr.Button("Process") | |
| greet_btn.click(fn=process, inputs=[cellid_input, image_input, path_input, sphere_radius, peak_threshold, xy_res, z_res, threshold_type, use_corrected_positions, screening_distance], outputs=[trace_output, image_output, plot_output, data_output, data_file_output], api_name="process") | |
| if __name__ == "__main__": | |
| demo.launch(server_name="0.0.0.0", share=False) | |