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| import gradio as gr | |
| #import tensorflow as tf | |
| import numpy as np | |
| import json | |
| from os.path import dirname, realpath, join | |
| import processing.pipeline_numpy as ppn | |
| # Load human-readable labels for ImageNet. | |
| current_dir = dirname(realpath(__file__)) | |
| def process(RawImage, CameraParameters, Debayer, Sharpening, Denoising): | |
| raw_img = RawImage | |
| if CameraParameters == "Microscope": | |
| black_level = [9.834368023181512e-06, 9.834368023181512e-06, 9.834368023181512e-06, 9.834368023181512e-06] | |
| white_balance = [-0.6567, 1.9673, 3.5304] | |
| colour_matrix = [-2.0338, 0.0933, 0.4157, -0.0286, 2.6464, -0.0574, -0.5516, -0.0947, 2.9308] | |
| elif CameraParameters == "Drone": | |
| #drone | |
| black_level = [0.0625, 0.0626, 0.0625, 0.0626] | |
| white_balance = [2.86653646, 1., 1.73079425] | |
| colour_matrix = [1.50768983, -0.33571374, -0.17197604, -0.23048614, | |
| 1.70698738, -0.47650126, -0.03119153, -0.32803956, 1.35923111] | |
| else: | |
| black_level = [0.0625, 0.0626, 0.0625, 0.0626] | |
| white_balance = [2.86653646, 1., 1.73079425] | |
| colour_matrix = [1.50768983, -0.33571374, -0.17197604, -0.23048614, | |
| 1.70698738, -0.47650126, -0.03119153, -0.32803956, 1.35923111] | |
| debayer = Debayer | |
| sharpening = Sharpening | |
| denoising = Denoising | |
| print(np.max(raw_img)) | |
| raw_img = (raw_img[:,:,:].astype(np.float64)/255.) | |
| img = ppn.processing(raw_img, black_level, white_balance, colour_matrix, | |
| debayer=debayer, sharpening=sharpening, denoising=denoising) | |
| print(np.max(img)) | |
| return img | |
| iface = gr.Interface( | |
| process, | |
| [gr.inputs.Image(),gr.inputs.Radio(["Microscope", "Drone"]),gr.inputs.Dropdown(["bilinear", "malvar2004", "menon2007"]), | |
| gr.inputs.Dropdown(["sharpening_filter", "unsharp_masking"]), | |
| gr.inputs.Dropdown(["gaussian_denoising", "median_denoising"])], | |
| "image", | |
| capture_session=True, | |
| examples=[ | |
| ["demo-files/car.png"], | |
| ["demo-files/micro.png"] | |
| ], | |
| title="static pipeline demo", | |
| description="You can select a sample raw image, the camera parameters and the pipeline configuration to process the raw image.") | |
| #if __name__ == "__main__": | |
| iface.launch() | |