Created app.py

app.py

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+# -*- coding: utf-8 -*-
+"""Image Conversion App .ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1GA79rJr1_J5bHa7sWxF1GtDqqaTznVia
+
+# ***Image Conversion from Simple image***
+> To 
+1. Edge Image
+2. Pencile sketch
+3. Painting
+4. Cartoon image
+
+###Step 1:- Import All libraries 
+Namely
+- Numpy (For storing Image)
+- Matplotlib (For Display image)
+- OpenCV (for Converting the image)
+"""
+
+# installing all imp libs to the machine
+#!pip install opencv_contrib_python
+
+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+import gradio as gr
+
+"""###Step 2:- Import and show the image
+for this we will be using opencv and matplotlib
+
+"""
+
+def read_image(Image):
+  '''
+  This Function is made to take image input from the user
+  Input: Path of the Image
+  Output: Image in RGB format
+  '''
+  img = cv2.imread(Image)
+  img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB) # As opencv read the image as BGR so we have to convert it to RGB
+  plt.imshow(img)
+  plt.show()
+  return img
+
+filename ="/content/to.jpeg"
+Image= read_image(filename)
+
+"""### Step 3:- Converting the Image to respective types
+Making diffrent Function for each work
+
+####4. Cartoon Image
+"""
+
+# create Edge
+def edge_mask(Image, line_size, Blur_value):
+  grey_img=cv2.cvtColor(Image,cv2.COLOR_RGB2GRAY)
+  grey_blur= cv2.medianBlur(grey_img, Blur_value)
+  edge_image= cv2.adaptiveThreshold(grey_blur, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, line_size, Blur_value)
+  return edge_image
+# line_size,Blur_value=7,7
+# edges= edge_mask(Image,line_size,Blur_value)
+# plt.imshow(edges, cmap="binary")
+# plt.show()
+
+#reduce Colour Palet
+def colour_quantization(Image, k):
+  data=np.float32(Image).reshape(-1,3)
+  critria= (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 20, 0.01)
+  ret, label, center= cv2.kmeans(data,k, None, critria, 10, cv2.KMEANS_RANDOM_CENTERS)
+  centers= np.uint8(center)
+  result=centers[label.flatten()]
+  result=result.reshape(Image.shape)
+  return result
+# Paint= colour_quantization(Image,10)
+# plt.imshow(Paint)
+# plt.show()
+# cv2.imwrite("final1.jpg",Paint)
+
+def cartoon(Paint,edges):
+  Blurred_img= cv2.bilateralFilter(Paint, d=8 ,sigmaColor=200, sigmaSpace=200)
+  Final=cv2.bitwise_and(Blurred_img,Blurred_img,mask=edges)
+  # plt.imshow(Final)
+  # plt.show()
+  # Final= cv2.cvtColor(Final, cv2.COLOR_RGB2BGR)
+  # cv2.imwrite("Final.jpg", Final)
+  return Final
+# cartoon()
+
+def Main_cartoon(Image,Line_size,Blur_value,Color_count):
+  edge_mask_img= edge_mask(Image, Line_size, Blur_value)
+  Paint_img=colour_quantization(Image, Color_count)
+  cartoon_img= cartoon(Paint_img,edge_mask_img)
+  # cartoon_img=cv2.cvtColor(cartoon_img, cv2.COLOR_RGB2BGR)
+  return cartoon_img
+
+x=Main_cartoon(Image,7,7,10)
+
+"""####3. Painting"""
+
+def Painting(Image, Colour_count):
+  Painting=colour_quantization(Image,Colour_count)
+  # Painting=cv2.cvtColor(Painting, cv2.COLOR_RGB2BGR)
+  return Painting
+
+y=Painting(Image,10)
+
+"""####2.Pencil Sketch"""
+
+def Pencil_sketch(Image):
+  grey_img=cv2.cvtColor(Image, cv2.COLOR_BGR2GRAY)
+  invert_img=cv2.bitwise_not(grey_img)
+  blur_img=cv2.GaussianBlur(invert_img, (111,111),0)
+  invblur_img=cv2.bitwise_not(blur_img)
+  sketch_img=cv2.divide(grey_img,invblur_img, scale=256.0)
+  return sketch_img
+
+z=Pencil_sketch(Image)
+
+"""####1.Edge Sketch"""
+
+def Edge_sketch(Image):
+  edge_img = cv2.Canny(Image,100,200)
+  edge_img = cv2.cvtColor(edge_img,cv2.COLOR_BGR2RGB)
+  return edge_img
+
+t=Edge_sketch(Image)
+
+"""###Step 4:- Testing"""
+
+plt.imshow(x)
+plt.show()
+cv2.imwrite("Final.jpg", x)
+
+plt.imshow(y)
+plt.show()
+cv2.imwrite("final1.jpg",y)
+
+plt.imshow(z)
+plt.show()
+cv2.imwrite("final2.jpg",z)
+
+plt.imshow(t)
+plt.show()
+cv2.imwrite("final3.jpg",t)
+
+"""### Step 5:- Gradio app and driver code
+
+#### Driver Code
+"""
+
+def Sketch_app(Image,Type,Color_count,Line_size,Blur_value):
+  if Type == "Cartoon":
+    Result = Main_cartoon(Image,Line_size,Blur_value,Color_count)
+  elif Type == "Painting":
+    Result = Painting(Image,Color_count)
+  elif Type == "Pencil sketch":
+    Result = Pencil_sketch(Image)
+  else:
+    Result = None
+  return Result
+
+"""#### Gradio app
+
+##### Installing and Importing Gradio
+As Gradio is a 3rd party library we have to install it in Our Run time before Executing
+"""
+
+#!pip install gradio
+
+
+
+Image_conversion = gr.Interface(
+    fn = Sketch_app,
+    inputs=[
+            gr.Image( tool="select",label="Image to Convert", show_label=True),
+            gr.Dropdown( choices = ["Pencil sketch","Painting","Cartoon"],label="Type to convert", show_label=True),
+            gr.Slider( minimum=5, maximum=20, value =10, step= 1,label="Number of colour to be used in photo ( use only in case of painting and cartoon)", show_label=True),
+            gr.Slider( minimum=5, maximum=10, value =7, step= 1,label="Blurr effect to be used in photo ( use only in case of cartoon)", show_label=True),
+            gr.Slider( minimum=5, maximum=10, value =7, step= 1,label="Thickness of edges to be used in photo ( use only in case of cartoon)", show_label=True)],
+    outputs= "image",
+    tittle = " Image Conversion App",
+    description = """This is an image conversion app we take a regular photo and convert it into Cartoon, Painting, Pencil sketch. it is purely python based used 
+    Gradio(for interfaceing), OpenCV (For image conversion), Numpy(for storing the image), Matplotlib (for displaying the image) """,
+    theme = "dark"
+)
+
+Image_conversion.launch()
+