diff --git a/Toonify/README.md b/Toonify/README.md
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+## HOW TO USE
+
+#### Using OpenCv ([link](./toonify-opencv.py))
+
+
+- To just view the image
+```python
+python3 toonify-opencv.py -i img_path
+```
+
+
+- To view and download the image 
+```python
+python3 toonify-opencv.py -i img_path -o download_path
+```
+
+#### Using Toonify-API(by DeepAI) 
+
+
+##### For local image ([link](./toonify-API-1.py))
+
+```python 
+python3 toonify-API-1.py -i img_path -k api_key
+
+```
+
+##### For URLS ([link](./toonify-API-2.py))
+
+```python 
+python3 toonify-API-2.py -i img_path -k api_key
+
+```
+
+> NOTE: The toonify image works well with .jpg format and might give some problem with other formats
+
+
+For more details on toonify API:
+
+[toonify API doc](https://deepai.org/machine-learning-model/toonify)
diff --git a/Toonify/toonify-API-1.py b/Toonify/toonify-API-1.py
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+import argparse
+import requests
+
+aq = argparse.ArgumentParser()
+aq.add_argument('-i', '--input', required=True, help="input image path")
+
+aq.add_argument('-k', '--apikey', required=True, help="api-key")
+
+args = vars(aq.parse_args())
+
+r = requests.post(
+    "https://api.deepai.org/api/toonify",
+    files={
+        'image': open(args['input'], 'rb'),
+    },
+    headers={'api-key': args['apikey']}
+)
+print(r.json()['output_url'])
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diff --git a/Toonify/toonify-API-2.py b/Toonify/toonify-API-2.py
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+import argparse
+import requests
+
+aq = argparse.ArgumentParser()
+aq.add_argument('-i', '--input', required=True, help="input image link")
+
+aq.add_argument('-k', '--apikey', required=True, help="api-key")
+
+args = vars(aq.parse_args())
+
+r = requests.post(
+    "https://api.deepai.org/api/toonify",
+    files={
+        'image': args['input'],
+    },
+    headers={'api-key': args['apikey']}
+)
+print(r.json()['output_url'])
diff --git a/Toonify/toonify-opencv.py b/Toonify/toonify-opencv.py
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+# importing libraries 
+import cv2 
+import numpy as np 
+import argparse
+
+aq = argparse.ArgumentParser()
+
+aq.add_argument('-i', '--input', required=True, help="input image path")
+
+aq.add_argument('-o', '--output', help="path where you want to download the image")
+
+args = vars(aq.parse_args())
+# reading image  
+img = cv2.imread(args['input']) 
+   
+# Edges 
+gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 
+gray = cv2.medianBlur(gray, 5) 
+edges = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C,  
+                                         cv2.THRESH_BINARY, 9, 9) 
+   
+# Cartoonization 
+color = cv2.bilateralFilter(img, 2, 250, 250) 
+cartoon = cv2.bitwise_or(color, color, mask=edges) 
+ 
+if(args['output']):
+	cv2.imwrite(args['output'], cartoon)
+
+
+cv2.imshow("Cartoon", cartoon) 
+cv2.waitKey(0) 
+cv2.destroyAllWindows() 
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