96 lines
2.8 KiB
Python
96 lines
2.8 KiB
Python
import cv2 as cv
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import numpy as np
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import h5py as h5
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db = None
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def init_train():
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''' Default init based on the train set `train.h5` '''
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init('train.h5')
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def init(path):
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''' initializes the database, must be called before any use '''
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global db
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db = h5.File(path, 'r')
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def needs_init():
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''' checks if the database has been initialized '''
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if db is None:
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print('db is none, please use init(path_to_db) first!')
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return db is None
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# Extract letter from a bounding box
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def extract_bb(img, bb):
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''' extracts a bounding box/letter from the given image '''
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# Get the bounding box
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rect = cv.minAreaRect(bb.astype(np.float32).transpose())
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# will be useful later, map center and size to ints
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center, size = tuple(map(int, rect[0])), tuple(map(int, rect[1]))
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# Calculate rotation matrix and rotate the image
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rot_matrix = cv.getRotationMatrix2D(center, rect[2], 1)
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rot_img = cv.warpAffine(img, rot_matrix, (img.shape[1], img.shape[0]))
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# bounding box is now axis aligned, and we can crop it
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print(size)
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cropped = cv.getRectSubPix(rot_img, size, center)
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return cropped
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def get_img(index):
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''' gets image from database '''
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if needs_init():
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return None
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names = list(db['data'].keys())
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im = names[index]
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return db['data'][im][:]
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def get_attrs(index):
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''' gets attribute dict from the database '''
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if needs_init():
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return None
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names = list(db['data'].keys())
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im = names[index]
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return db['data'][im].attrs
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def get_avg_color(img, mask):
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'''
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gets avg color from an image that is underneath a mask,
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img and mask needs to be of same size(in x,y) but img can
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have any third dimension size it want(usually 3 for rgb or 1 for grayscale)
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mask needs to be of shape(img.width, img.height, 1)
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'''
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sx, sy, sw = img.shape
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mx, my = mask.shape
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if sx != mx or sy != my:
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print('Image and mask size doesnt match!')
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return None
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avg = np.zeros(sw, dtype=np.float32)
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count = 0.0
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for x in range(sx):
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for y in range(sy):
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m = mask[x, y]
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avg += img[x, y] * m
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count += m
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avg /= count
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return avg
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def calc_score(img, mask, avg_color):
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'''
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Calculates the score for each mask with each color
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'''
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sx, sy, sw = img.shape
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mx, my = mask.shape
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if sx != mx or sy != my:
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print('Image and mask size doesnt match!')
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return 0.0
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if sw != avg_color.shape[0]:
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print('Image width doesnt match color width!')
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return 0.0
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score = 0.0
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for x in range(sx):
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for y in range(sy):
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m = 0.5 - mask[x, y]
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diff = img[x, y] - avg_color
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mag = np.sqrt(diff.dot(diff)) # calculate magnitude
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score += mag * m
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return score
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