I want to make a function which generate a dataset, The object will be place on the black image at different position with different angle, different size and place randomly maximum up to 20 time in image. and Save the x,y and angle position in the text file.
The following image is for five objects at different position and angle.
import numpy as np
import cv2
patch=cv2.imread('imagersult.png')
img = np.zeros((2048, 2048, 1), dtype = "uint8")
Here is how you can use the scipy.ndimage module to rotate your patches:
import numpy as np
import cv2
from random import randrange
from scipy import ndimage
def patch_img(img, patch, amt=5):
h, w, _ = img.shape
for _ in range(amt):
p = ndimage.rotate(patch, randrange(360))
p_h, p_w, _ = p.shape
x = randrange(w - p_w)
y = randrange(h - p_h)
seg = img[y: y + p_h, x: x + p_w]
seg[:] = cv2.bitwise_xor(seg, p)
patch = cv2.imread('imagersult.png')
img = np.zeros((2048, 2048, 3), dtype="uint8")
patch_img(img, patch)
cv2.imshow("Image", img)
cv2.waitKey(0)
Outputs for multiple runs:
For grayscale and variation in size of the patches:
import numpy as np
import cv2
from random import randrange, uniform
from scipy import ndimage
def patch_img(img, patch, amt=5):
h, w = img.shape
min_scale = 0.5
max_scale = 2
for _ in range(amt):
patch_h, patch_w = patch.shape
scale = uniform(min_scale, max_scale)
p = ndimage.rotate(cv2.resize(patch, (int(patch_w * scale), int(patch_h * scale))), randrange(360))
p_h, p_w = p.shape
x = randrange(w - p_w)
y = randrange(h - p_h)
seg = img[y: y + p_h, x: x + p_w]
seg[:] = cv2.bitwise_xor(seg, p)
patch = cv2.imread('imagersult.png', 0)
img = np.zeros((2048, 2048), dtype="uint8")
patch_img(img, patch)
cv2.imshow("Image", img)
cv2.imwrite("result.png", img)
cv2.waitKey(0)
Sample output:
