Functions
def	crop_square (img, size, interpolation=cv2.INTER_AREA)

def	patch_square (crop_img, img, interpolation=cv2.INTER_AREA)

Variables
string	trieres_lib = os.environ['cFpRootDir'] + "HOST/vision/warp_transform/languages/python/build"

int	height = 256

int	num_frame = 1

string	image_in_filename = os.environ['cFpRootDir'] + "ROLE/vision/hls/warp_transform/test/512x512.png"

string	image_out_filename = image_in_filename + "_fpga_points_out_frame_" + str(num_frame) + ".png"

bool	ROI = False

	image = cv2.imread(image_in_filename, cv2.IMREAD_UNCHANGED)

	image_big = image

tuple	dim = (width, height)

int	total_size = height * width

	input_array = image

	output_array = _trieres_warp_transform_numpi.warp_transform(input_array, total_size, "10.12.200.122", "2718")

	output_array_2d = np.reshape(output_array, (height, width))

Function Documentation

◆ crop_square()

def test_warp_transform_numpi.crop_square	(	img,
		size,
		interpolation = `cv2.INTER_AREA`
	)

Definition at line 47 of file test_warp_transform_numpi.py.

 def crop_square(img, size, interpolation=cv2.INTER_AREA):
     h, w = img.shape[:2]
     print("h="+str(h))
     print("w="+str(w))
     min_size = np.amin([h,w])
     print("min_size="+str(min_size))
  
     # Centralize and crop
     crop_img = img[int(h/2-min_size/2):int(h/2+min_size/2), int(w/2-min_size/2):int(w/2+min_size/2)]
     y1=10
     y2=y1+100
     x1=10
     x2=x1+100
     roi = crop_img[y1:y2, x1:x2]
     resized = cv2.resize(roi , (size, size), interpolation=interpolation)
  
     return resized
  
  

◆ patch_square()

def test_warp_transform_numpi.patch_square	(	crop_img,
		img,
		interpolation = `cv2.INTER_AREA`
	)

Definition at line 66 of file test_warp_transform_numpi.py.

 def patch_square(crop_img, img, interpolation=cv2.INTER_AREA):
     h, w = img.shape[:2]
     print("h="+str(h))
     print("w="+str(w))
     min_size = np.amin([h,w])
     print("min_size="+str(min_size))
  
     # Centralize and patch
     img[int(h/2-min_size/2):int(h/2+min_size/2), int(w/2-min_size/2):int(w/2+min_size/2)] = crop_img
  
     return img