import gradio as gr from utils import * import cv2 import numpy as np import matplotlib.pyplot as plt import io def inference(img, template, angel): color_image = cv2.imread(img.name, cv2.IMREAD_COLOR) HSV_image = cv2.cvtColor(color_image, cv2.COLOR_BGR2HSV) selected_harmomic_scheme = HarmonicScheme(str(template), int(angel)) new_HSV_image = selected_harmomic_scheme.hue_shifted(HSV_image, num_superpixels=-1) # Convert HSV to BGR result_image = cv2.cvtColor(new_HSV_image, cv2.COLOR_HSV2BGR) # Compute shifted histogram histo_1 = count_hue_histogram(HSV_image) histo_2 = count_hue_histogram(new_HSV_image) # Create Hue Plots fig1 = plothis(histo_1, selected_harmomic_scheme, "Source Hue") fig_1_cv = get_img_from_fig(fig1) fig2 = plothis(histo_2, selected_harmomic_scheme, "Target Hue") fig_2_cv = get_img_from_fig(fig2) hue_plots = np.concatenate((fig_1_cv, fig_2_cv), axis=1) cv2.imwrite('hue.jpg', hue_plots) cv2.imwrite('result_image.jpg', result_image) return ['result_image.jpg', 'hue.jpg'] title = 'Color Harmonization' description = 'Compute Color Harmonization with different templates based on Color Harmonization paper by Daniel Cohen-Or et al. More metrics for user interfaces on https://interfacemetrics.aalto.fi' article = "

" examples = [['./examples/aim_interface.png', "V", 25], ['./examples/esfahan_unsplash.jpeg', "I", 352]] # css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}" gr.Interface( inference, [gr.inputs.Image(type='file', label='Original Image'), gr.inputs.Dropdown(["X", "Y", "T", "I", "mirror_L", "L", "V", "i"], default="X", label="Template"), gr.inputs.Slider(0, 359, label="Angle")], [gr.outputs.Image(type='file', label='Harmonized Image'), gr.outputs.Image(type='file', label='Hue')], title=title, description=description, article=article, examples=examples, # css=css, ).launch(debug=True, enable_queue=True)