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import cv2
import numpy as np
def change_image_color_format(file_path, format_type, angle=0,factor=1.5):
img = cv2.imread(file_path)
if format_type.lower() == 'rgb':
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
return img_rgb
elif format_type.lower() == 'bgr':
img_bgr = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
return img_bgr
elif format_type.lower() == 'grayscale':
grayscale_img = cv2.cvtColor(img, cv2.IMREAD_GRAYSCALE)
return grayscale_img
elif format_type.lower() == 'rotate':
if angle != 0:
img = rotate_image(img, angle)
return img
elif format_type == "increase_brightness":
brightened_img = increase_brightness(img, factor)
return brightened_img
elif format_type.lower() == "blur_image":
imgBlur = cv2.GaussianBlur(img,(7,7),0)
return imgBlur
elif format_type.lower() == "resize_image":
resized_image = resize_image(img,width=1000,height=1000)
return resized_image
# Function to rotate an OpenCV image (numpy.ndarray)
def rotate_image(image, angle):
(h, w) = image.shape[:2]
center = (w // 2, h // 2)
M = cv2.getRotationMatrix2D(center, angle, 1.0)
rotated_image = cv2.warpAffine(image, M, (w, h))
return rotated_image
# Function to increase the brightness of an image
def increase_brightness(image, factor=1.2):
image = np.array(image, dtype=np.float32)
brightened_image = cv2.multiply(image, np.array([factor, factor, factor], dtype=np.float32))
brightened_image = np.clip(brightened_image, 0, 255).astype(np.uint8)
return brightened_image
def resize_image(img,width = 200,height = 200):
imgResize = cv2.resize(img,(width,height))
return imgResize
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