update code

app.py

@@ -1,26 +1,22 @@
-'''
-Sometimes you just want to take an image from your database and see how it changes by running different image processing functions, to find the best starting point for your computer vision application. In this Hugging Face space, I have included various pattern recognition functions that can easily be applied to your input images, so you can see the output of each function. I will continue to update this space with additional modes, methods, and deep learning frameworks/models, to make them easy to use for demonstration purposes. Please let me know if you would like me to include any other specific functionality.
-
-'''
-
 import gradio as gr
-from  src.threshold_methods import threshold_methods
+from src.threshold_methods import threshold_methods
 from src.yolo import yolo
 from src.video_processing import video_processing
 import cv2
 
 new_outputs = [
-gr.outputs.Image(type="numpy", label="Output Image"), 
-gr.outputs.Textbox(type="text", label="My HuggingFace URL"), 
-gr.outputs.Textbox(type="text", label="My linkedin URL"), 
-gr.outputs.Textbox(type="text", label="info") 
+    gr.outputs.Image(type="numpy", label="Output Image"), 
+    gr.outputs.Textbox(type="text", label="HuggingFace URL"), 
+    gr.outputs.Textbox(type="text", label="LinkedIn URL"), 
+    gr.outputs.Textbox(type="text", label="Info") 
 ]
+
 def show_image():
     img = cv2.imread('files/huggingface.png')   
     text1 = 'https://huggingface.co/spaces/pirahansiah/ComputerVision' 
     text2 = 'https://www.linkedin.com/in/pirahansiah/' 
-    text3 = ' Sometimes you just want to take an image from your database and see how it changes by running different image processing functions, to find the best starting point for your computer vision application. In this Hugging Face space, I have included various pattern recognition functions that can easily be applied to your input images, so you can see the output of each function. I will continue to update this space with additional modes, methods, and deep learning frameworks/models, to make them easy to use for demonstration purposes. Please let me know if you would like me to include any other specific functionality.    '
-    return img,text1,text2,text3
+    text3 = 'Sometimes you want to take an image from your database and see how it changes by applying different image processing functions, to find the best starting point for your computer vision application. In this Hugging Face space, I have included various pattern recognition functions that can be easily applied to your input images, allowing you to see the output of each function. I will continue to update this space with additional modes, methods, and deep learning frameworks/models to make them easy to use for demonstration purposes. Please let me know if you would like any other specific functionality included.'
+    return img, text1, text2, text3
 
 HuggingFace = gr.Interface(
     fn=show_image,
@@ -28,16 +24,10 @@ HuggingFace = gr.Interface(
     inputs=[],
     outputs=new_outputs,       
     hide_controls=True,
-    hide_inputs=True,
-    show_submit_buttom=False,
-    show_clear=False,
-    show_generate=False,
-    allow_flagging=False,
     title="Computer Vision and Deep Learning by Farshid PirahanSiah",
 )
 
 gr.TabbedInterface(
-    [HuggingFace,threshold_methods,yolo,video_processing],
-    tab_names=['HuggingFace','Thresholding Image Segmentation','YOLO','Video Multi Objects tracking']
+    [HuggingFace, threshold_methods, yolo, video_processing],
+    tab_names=['HuggingFace', 'Thresholding Image Segmentation', 'YOLO', 'Video Multi-Object Tracking']
 ).queue().launch()
-