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import cv2
import numpy as np
import shutil
import os
from os.path import join as pjoin
def segment_img(org, segment_size, output_path, overlap=100):
if not os.path.exists(output_path):
os.mkdir(output_path)
height, width = np.shape(org)[0], np.shape(org)[1]
top = 0
bottom = segment_size
segment_no = 0
while top < height and bottom < height:
segment = org[top:bottom]
cv2.imwrite(os.path.join(output_path, str(segment_no) + '.png'), segment)
segment_no += 1
top += segment_size - overlap
bottom = bottom + segment_size - overlap if bottom + segment_size - overlap <= height else height
def clipping(img, components, pad=0, show=False):
"""
:param adjust: shrink(negative) or expand(positive) the bounding box
:param img: original image
:param corners: ((column_min, row_min),(column_max, row_max))
:return: list of clipping images
"""
clips = []
for component in components:
clip = component.compo_clipping(img, pad=pad)
clips.append(clip)
if show:
cv2.imshow('clipping', clip)
cv2.waitKey()
return clips
def dissemble_clip_img_hollow(clip_root, org, compos):
if os.path.exists(clip_root):
shutil.rmtree(clip_root)
os.mkdir(clip_root)
cls_dirs = []
bkg = org.copy()
hollow_out = np.ones(bkg.shape[:2], dtype=np.uint8) * 255
for compo in compos:
cls = compo.category
c_root = pjoin(clip_root, cls)
c_path = pjoin(c_root, str(compo.id) + '.jpg')
if cls not in cls_dirs:
os.mkdir(c_root)
cls_dirs.append(cls)
clip = compo.compo_clipping(org)
cv2.imwrite(c_path, clip)
col_min, row_min, col_max, row_max = compo.put_bbox()
hollow_out[row_min: row_max, col_min: col_max] = 0
bkg = cv2.merge((bkg, hollow_out))
cv2.imwrite(os.path.join(clip_root, 'bkg.png'), bkg)
def dissemble_clip_img_fill(clip_root, org, compos, flag='most'):
def average_pix_around(pad=6, offset=3):
up = row_min - pad if row_min - pad >= 0 else 0
left = col_min - pad if col_min - pad >= 0 else 0
bottom = row_max + pad if row_max + pad < org.shape[0] - 1 else org.shape[0] - 1
right = col_max + pad if col_max + pad < org.shape[1] - 1 else org.shape[1] - 1
average = []
for i in range(3):
avg_up = np.average(org[up:row_min - offset, left:right, i])
avg_bot = np.average(org[row_max + offset:bottom, left:right, i])
avg_left = np.average(org[up:bottom, left:col_min - offset, i])
avg_right = np.average(org[up:bottom, col_max + offset:right, i])
average.append(int((avg_up + avg_bot + avg_left + avg_right)/4))
return average
def most_pix_around(pad=6, offset=2):
up = row_min - pad if row_min - pad >= 0 else 0
left = col_min - pad if col_min - pad >= 0 else 0
bottom = row_max + pad if row_max + pad < org.shape[0] - 1 else org.shape[0] - 1
right = col_max + pad if col_max + pad < org.shape[1] - 1 else org.shape[1] - 1
most = []
for i in range(3):
val = np.concatenate((org[up:row_min - offset, left:right, i].flatten(),
org[row_max + offset:bottom, left:right, i].flatten(),
org[up:bottom, left:col_min - offset, i].flatten(),
org[up:bottom, col_max + offset:right, i].flatten()))
# print(val)
# print(np.argmax(np.bincount(val)))
most.append(int(np.argmax(np.bincount(val))))
return most
if os.path.exists(clip_root):
shutil.rmtree(clip_root)
os.mkdir(clip_root)
cls_dirs = []
bkg = org.copy()
for compo in compos:
cls = compo.category
c_root = pjoin(clip_root, cls)
c_path = pjoin(c_root, str(compo.id) + '.jpg')
if cls not in cls_dirs:
os.mkdir(c_root)
cls_dirs.append(cls)
clip = compo.compo_clipping(org)
cv2.imwrite(c_path, clip)
col_min, row_min, col_max, row_max = compo.put_bbox()
if flag == 'average':
color = average_pix_around()
elif flag == 'most':
color = most_pix_around()
cv2.rectangle(bkg, (col_min, row_min), (col_max, row_max), color, -1)
cv2.imwrite(os.path.join(clip_root, 'bkg.png'), bkg)
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