leuschnm commited on
Commit
494c823
·
1 Parent(s): 5805ca0

added demo + examples images

Browse files
Files changed (4) hide show
  1. IMG_1.jpg +0 -0
  2. IMG_2.jpg +0 -0
  3. IMG_3.jpg +0 -0
  4. app.py +24 -4
IMG_1.jpg ADDED
IMG_2.jpg ADDED
IMG_3.jpg ADDED
app.py CHANGED
@@ -1,7 +1,27 @@
 
1
  import gradio as gr
2
 
3
- def greet(name):
4
- return "Hello " + name + "!!"
5
 
6
- iface = gr.Interface(fn=greet, inputs="text", outputs="text", title="Crowd Counting with Mf Attention")
7
- iface.launch()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import numpy as np
2
  import gradio as gr
3
 
4
+ def flip_image(x):
5
+ return (1000, np.zeros((100, 100))
6
 
7
+ with gr.Blocks() as demo:
8
+ gr.Markdown("""
9
+ # Crowd Counting based on SASNet
10
+
11
+ We implemented a image crowd counting model with VGG16 following the paper of Song et. al (2021).
12
+
13
+ ## References
14
+ 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).
15
+ """)
16
+ image_button = gr.Button("Count the Crowd!")
17
+ with gr.Row():
18
+ with gr.Column():
19
+ image_input = gr.Image(type="pil")
20
+ gr.Examples(["IMG_1.jpg", "IMG_2.jpg", "IMG_3.jpg"], image_input)
21
+ with gr.Column():
22
+ image_output = gr.Image()
23
+ text_output = gr.Label()
24
+
25
+ image_button.click(flip_image, inputs=image_input, outputs=[text_output, image_output])
26
+
27
+ demo.launch()