import gradio as gr import os import random from src.model import simlarity_model as model from src.similarity.similarity import Similarity similarity = Similarity() models = similarity.get_models() def check(img_main, img_1, img_2, img_3, img_4, img_5, img_6, img_7, img_8, img_9, img_10): result = similarity.check_similarity([img_main, img_1, img_2, img_3, img_4, img_5, img_6, img_7, img_8, img_9, img_10], models[2]) return result with gr.Blocks() as demo: gr.Markdown('Checking Image Similarity') img_main = gr.Text(label='Main Image', placeholder='https://myimage.jpg') gr.Markdown('Images to check') # img_list = [] # for i in range(10): # img_list.append(gr.Text(label='{} st Image'.format(i), placeholder='https://myimage_1.jpg', i)) img_1 = gr.Text(label='1st Image', placeholder='https://myimage_1.jpg') print("img1: ", img_1) img_2 = gr.Text(label='2nd Image', placeholder='https://myimage_2.jpg') img_3 = gr.Text(label='3st Image', placeholder='https://myimage_1.jpg') img_4 = gr.Text(label='4nd Image', placeholder='https://myimage_2.jpg') img_5 = gr.Text(label='5st Image', placeholder='https://myimage_1.jpg') img_6 = gr.Text(label='6nd Image', placeholder='https://myimage_2.jpg') img_7 = gr.Text(label='7st Image', placeholder='https://myimage_1.jpg') img_8 = gr.Text(label='8nd Image', placeholder='https://myimage_2.jpg') img_9 = gr.Text(label='9st Image', placeholder='https://myimage_1.jpg') img_10 = gr.Text(label='10st Image', placeholder='https://myimage_2.jpg') # img_list = [img_1, img_2, img_3, img_4, img_5, img_6, img_7, img_8, img_9, img_10] # for i in range(len(img_list)): # img # gr.Markdown('Choose the model') # model = gr.Dropdown([m.name for m in models], label='Model', type='index') # print("model name:", model) gallery = gr.Gallery( label="Generated images", show_label=False, elem_id="gallery" ).style(grid=[10], height="auto") output_metric = gr.Text(label='output metrics') submit_btn = gr.Button('Check Similarity') submit_btn.click(fn=check,inputs=[img_main, img_1, img_2, img_3, img_4, img_5, img_6, img_7, img_8, img_9, img_10], outputs=gallery, api_name="predict") demo.launch()