| import numpy as np | |
| import gradio as gr | |
| def flip_image(x): | |
| return (1000, np.zeros((100, 100))) | |
| with gr.Blocks() as demo: | |
| gr.Markdown(""" | |
| # Crowd Counting based on SASNet | |
| We implemented a image crowd counting model with VGG16 following the paper of Song et. al (2021). | |
| ## References | |
| Song, Q., Wang, C., Wang, Y., Tai, Y., Wang, C., Li, J., … Ma, J. (2021). To Choose or to Fuse? Scale Selection for Crowd Counting. The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21). | |
| """) | |
| image_button = gr.Button("Count the Crowd!") | |
| with gr.Row(): | |
| with gr.Column(): | |
| image_input = gr.Image(type="pil") | |
| gr.Examples(["IMG_1.jpg", "IMG_2.jpg", "IMG_3.jpg"], image_input) | |
| with gr.Column(): | |
| image_output = gr.Image() | |
| text_output = gr.Label() | |
| image_button.click(flip_image, inputs=image_input, outputs=[text_output, image_output]) | |
| demo.launch() | |