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# file to crop object from image and enhance it.
import cv2
import numpy as np
import logging
# Configure the logger
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s - %(levelname)s - %(message)s",
filename="logs.log",
)
# Create a logger
logger = logging.getLogger("pipline")
def croped_images(image,merged_boundary_boxes):
""" Crop object from original image
Args:
image (numpy array): get numpy array of image which has 3 channels
merged_boundary_boxes (json array): get json array
Returns:
croped_images_list(list of numpy array): returns list which has croped images
single_object_images(list of numpy array): returns list which has single object images
"""
logger.info('croped images function is called...')
try:
croped_images_list = []
single_object_images = []
for data in merged_boundary_boxes:
crop_image = image[data['merged_boundries']['top_left'][1]:data['merged_boundries']['bottom_right'][1],data['merged_boundries']['top_left'][0]:data['merged_boundries']['bottom_right'][0]]
croped_images_list.append(crop_image)
for object in data['actual_boundries']:
if object['class']=='person':
crop_object= image[object['top_left'][1]:object['bottom_right'][1],object['top_left'][0]:object['bottom_right'][0]]
single_object_images.append(crop_object)
return croped_images_list,single_object_images
except Exception as e:
logger.error("Something went wrong in croped image function...")
logger.error(e)
def image_enhancements(croped_images_list,single_object_images):
""" Enhance cropped image using openCV techniques
Args:
croped_images_list (list numpy array): croped images list
single_object_images (list numpy array): single object images list
Returns:
enhanced croped images: returns enhanced images
enhanced single_object_images: returns enhanced images
"""
logger.info("image enhance function is called...")
try:
enhanced_images = []
enhanced_single_object_images = []
for image in croped_images_list:
# resize the image
res = cv2.resize(image,(500*image.shape[1]//image.shape[0],500), interpolation = cv2.INTER_CUBIC)
# brightness and contrast
brightness = 16
contrast = 0.95
res2 = cv2.addWeighted(res, contrast, np.zeros(res.shape, res.dtype), 0, brightness)
# Sharpen the image
kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
sharpened_image = cv2.filter2D(res2, -1, kernel)
#append in the list
enhanced_images.append(sharpened_image)
for image in single_object_images:
# resize the image
res = cv2.resize(image,(500*image.shape[1]//image.shape[0],500), interpolation = cv2.INTER_CUBIC)
# brightness and contrast
brightness = 16
contrast = 0.95
res2 = cv2.addWeighted(res, contrast, np.zeros(res.shape, res.dtype), 0, brightness)
# Sharpen the image
kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
sharpened_image = cv2.filter2D(res2, -1, kernel)
#append enhnaced single object image
enhanced_single_object_images.append(sharpened_image)
return enhanced_images,enhanced_single_object_images
except Exception as e:
logger.error("Something went wrong in image enhancements function...")
logger.error(e)
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