#!/usr/bin/env python
# coding: utf-8

# ![](cat-crisp.webp)
# 
# # Blurry
# 
# Kevin Walchko
# 
# ---
# ```

# In[2]:


# reload library
get_ipython().run_line_magic('load_ext', 'autoreload')
get_ipython().run_line_magic('autoreload', '2')


# In[3]:


import numpy as np
import cv2
from matplotlib import pyplot as plt

np.set_printoptions(precision=3)
np.set_printoptions(suppress=True)


# In[4]:


def blurry(image, threshold=100.0):
    """
    Given an image and threshold, returns if image is blurry and its value
    
    Args:
      image: opencv grayscale image
      threshold: blur threshold value, below this value an image is considered
                 to be blurry
    Return:
      blurry: True/False
      value: numeric value of blurriness
      
    Reference: https://pyimagesearch.com/2015/09/07/blur-detection-with-opencv/
    """
    val = cv2.Laplacian(image, cv2.CV_64F).var()
    val = int(val)
    if val < threshold:
        return True, val
    return False, val


# In[5]:


cat = cv2.imread("cat-blurry.webp",0)
plt.imshow(cat, cmap="gray")
plt.axis("off")
plt.title(f"Blurry: {blurry(cat, 300)}");


# In[6]:


cat = cv2.imread("cat-crisp.webp",0)
plt.imshow(cat, cmap="gray")
plt.axis("off")
plt.title(f"Blurry: {blurry(cat, 300)}");


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