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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() |