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# Copyright 2022-present NAVER Corp.
# CC BY-NC-SA 4.0
# Available only for non-commercial use
from pdb import set_trace as bb
import numpy as np
from PIL import Image, ImageOps, ImageEnhance
def grab( data, *fields ):
''' Called to extract fields from a dictionary
'''
if isinstance(data, dict):
res = []
for f in fields:
res.append( data[f] )
return res[0] if len(fields) == 1 else tuple(res)
else: # or it must be the img directly
assert fields == ('img',) and isinstance(data, (np.ndarray, Image.Image)), \
f"data should be an image, not {type(data)}!"
return data
def update( data, **fields):
''' Called to update the img_and_label
'''
if isinstance( data, dict):
if 'homography' in fields and 'homography' in data:
data['homography'] = fields.pop('homography') @ data['homography']
data.update(fields)
if 'img' in fields:
data['imsize'] = data['img'].size
return data
else: # or it must be the img directly
return fields['img']
def rand_log_uniform(rng, a, b):
return np.exp(rng.uniform(np.log(a),np.log(b)))
def translate(tx, ty):
return np.float32(((1,0,tx),(0,1,ty,),(0,0,1)))
def rotate(angle):
return np.float32(((np.cos(angle),-np.sin(angle),0),(np.sin(angle),np.cos(angle),0),(0,0,1)))
def is_pil_image(img):
return isinstance(img, Image.Image)
def homography_from_4pts(pts_cur, pts_new):
"pts_cur and pts_new = 4x2 point array, in [(x,y),...] format"
matrix = []
for p1, p2 in zip(pts_new, pts_cur):
matrix.append([p1[0], p1[1], 1, 0, 0, 0, -p2[0] * p1[0], -p2[0] * p1[1]])
matrix.append([0, 0, 0, p1[0], p1[1], 1, -p2[1] * p1[0], -p2[1] * p1[1]])
A = np.matrix(matrix, dtype=np.float)
B = np.array(pts_cur).reshape(8)
homography = np.dot(np.linalg.pinv(A), B)
homography = tuple(np.array(homography).reshape(8))
#print(homography)
return homography
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