Update app.py

app.py

@@ -46,4 +46,4 @@ def crowd(img):
 outputs = gr.outputs.Textbox(type="auto", label="Estimated crowd density:")
 inputs = gr.inputs.Image(type="numpy", label="Input the image here:")
 
-gr.Interface(fn=crowd, inputs=inputs, outputs=outputs, allow_flagging="never", examples=["IMG_5.jpg", "IMG_10.jpg"], title = "CANNet Crowd Counting Model", description = "CANNet crowd counting model by Lui, Salzmann, and Fua in their paper Context-Aware Crowd Counting publish in The IEEE Conference on Computer Vision and Pattern Recognition (CPVR) on June 2019. The GitHub repository for the PyTorch implementation can be found in https://github.com/weizheliu/Context-Aware-Crowd-Counting.").launch(inbrowser=True)
+gr.Interface(fn=crowd, inputs=inputs, outputs=outputs, allow_flagging="never", examples=["IMG_5.jpg", "IMG_10.jpg"], title = "CANNet Crowd Counting Model", description = "CANNet crowd counting model by Lui, Salzmann, and Fua in their paper Context-Aware Crowd Counting publish in The IEEE Conference on Computer Vision and Pattern Recognition (CPVR) on June 2019. The GitHub repository for the PyTorch implementation can be found in https://github.com/weizheliu/Context-Aware-Crowd-Counting. Please input the image and click submit to use the model and know the estimated crowd count in the image.").launch(inbrowser=True)