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img_process.py
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img_process.py
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import cv2
import numpy as np
from message import Message
from PIL import Image
class ProcessImage(object):
def __init__(self, msg, img_seq):
self.frame_width = msg.frame_width
self.frame_height = msg.frame_height
frame_width = self.frame_width
frame_height = self.frame_height
left = frame_width / 2
up = frame_height / 2
right = frame_width / 2
low = frame_height / 2
for img in img_seq:
im = Image.fromarray(np.uint8(img))
bbox = im.getbbox()
if bbox == None:
continue
if bbox[0] < left:
left = bbox[0]
if bbox[1] < up:
up = bbox[1]
if bbox[2] > right:
right = bbox[2]
if bbox[3] > low:
low = bbox[3]
upper_left = (left, up)
lower_right = (right, low)
upper_left_p = (frame_width - upper_left[0], frame_height - upper_left[1])
lower_right_p = (frame_width - lower_right[0], frame_height - lower_right[1])
self.bbox_crop = (min(upper_left[0], lower_right[0], upper_left_p[0], lower_right_p[0]),
min(upper_left[1], lower_right[1], upper_left_p[1], lower_right_p[1]),
max(upper_left[0], lower_right[0], upper_left_p[0], lower_right_p[0]),
max(upper_left[1], lower_right[1], upper_left_p[1], lower_right_p[1]))
self.box_size = (self.bbox_crop[2] - self.bbox_crop[0],
self.bbox_crop[3] - self.bbox_crop[1])
self.process_scale = 224.0 / max(self.box_size)
self.new_size = (int(self.box_size[0] * self.process_scale),
int(self.box_size[1] * self.process_scale))
return
def process_image(self, img, debug=False):
im = Image.fromarray(np.uint8(img))
im = im.crop(self.bbox_crop)
paste_im = im.resize(self.new_size)
im = Image.new('RGB', (224, 224))
im.paste(paste_im, (112 - paste_im.size[0] // 2, 112 - paste_im.size[1] // 2))
if debug:
return np.array(im)
else:
im = np.array(im) / 255.0
im = im[:, :, 0]
im = np.expand_dims(im, axis = 2)
return im
def reverse_process_image(self, img, debug=False):
im = Image.fromarray(np.uint8(img))
new_crop = (112 - self.new_size[0] // 2,
112 - self.new_size[1] // 2,
112 + int(np.ceil(self.new_size[0] / 2)),
112 + int(np.ceil(self.new_size[1] / 2)))
im = im.crop(new_crop)
paste_im = im.resize(self.box_size)
im = Image.new('RGB', (self.frame_width, self.frame_height))
im.paste(paste_im, (self.bbox_crop[0], self.bbox_crop[1]))
if debug:
return np.array(im)
else:
im = np.array(im) / 255.0
im = im[:, :, 0]
im = np.expand_dims(im, axis = 2)
return im
class DrawGroupShape(object):
def __init__(self, msg):
self.H = msg.H
self.dataset = msg.dataset
self.frame_width = msg.frame_width
self.frame_height = msg.frame_height
self.center_set = False
self.aug_set = False
return
def coordinate_transform(self, coord):
# Transform the coordinates from metric space into pixel space
# Units are now pixels instead of meters after the transformation.
pt = np.matmul(np.linalg.inv(self.H), [[coord[0]], [coord[1]], [1.0]])
x = pt[0][0] / pt[2][0]
y = pt[1][0] / pt[2][0]
if self.dataset == 'ucy':
tmp_y = y
y = self.frame_width / 2 + x
x = self.frame_height / 2 - tmp_y
x = int(round(x))
y = int(round(y))
return (y, x)
def set_center(self, vertice_seq):
self.center_set = True
vertices = vertice_seq[-1]
center = [0, 0]
for v in vertices:
center[0] += v[0]
center[1] += v[1]
center[0] = center[0] / float(len(vertices))
center[1] = center[1] / float(len(vertices))
center = self.coordinate_transform(center)
self.center_offset = (self.frame_width / 2 - center[0],
self.frame_height / 2 - center[1])
return
def set_aug(self, angle=None, trans=None):
self.aug_set = True
if angle is None:
self.aug_angle = np.random.choice(360)
else:
self.aug_angle = angle
if trans is None:
self.aug_trans = (0, 0)
else:
self.aug_trans = trans
return
def move_center(self, coord):
x = coord[0] + self.center_offset[0]
y = coord[1] + self.center_offset[1]
return (int(x), int(y))
def reverse_move_center(self, coord):
x = coord[0] - self.center_offset[0]
y = coord[1] - self.center_offset[1]
return (int(x), int(y))
def reverse_move_center_img(self, img):
M = np.array([[1, 0, -self.center_offset[0]], [0, 1, -self.center_offset[1]]])
rst = cv2.warpAffine(img, M, (self.frame_width, self.frame_height))
return rst
def aug_transform(self, coord):
x = coord[0] + self.aug_trans[0]
y = coord[1] + self.aug_trans[1]
x -= self.frame_width / 2
y -= self.frame_height / 2
nx = np.cos(self.aug_angle) * x - np.sin(self.aug_angle) * y
ny = np.sin(self.aug_angle) * x + np.cos(self.aug_angle) * y
nx += self.frame_width / 2
ny += self.frame_height / 2
return (int(nx), int(ny))
def reverse_aug_transform(self, coord):
x = coord[0]
y = coord[1]
x -= self.frame_width / 2
y -= self.frame_height / 2
nx = np.cos(-self.aug_angle) * x - np.sin(-self.aug_angle) * y
ny = np.sin(-self.aug_angle) * x + np.cos(-self.aug_angle) * y
nx += self.frame_width / 2
ny += self.frame_height / 2
return (int(nx) - self.aug_trans[0], int(ny) - self.aug_trans[1])
def reverse_aug_transform_img(self, img):
M = np.array([[1.0, 0, -self.aug_trans[0]],
[0, 1.0, -self.aug_trans[1]]])
img = cv2.warpAffine(img, M, (self.frame_width, self.frame_height))
M = cv2.getRotationMatrix2D((self.frame_width / 2, self.frame_height / 2),
-self.aug_angle / np.pi * 180, 1)
img = cv2.warpAffine(img, M, (self.frame_width, self.frame_height))
return img
def draw_group_shape(self, vertices, frame, center=False, aug=False):
convex_hull_vertices = []
for i, elem in enumerate(vertices):
coord = self.coordinate_transform(elem)
if center and self.center_set:
coord = self.move_center(coord)
elif center and (not self.center_set):
print('Warning! Centering parameters not set so not performed!')
if aug and self.aug_set:
coord = self.aug_transform(coord)
elif aug and (not self.aug_set):
print('Warning! Augmentation parameterss not set so not performed!')
convex_hull_vertices.append(coord)
cv2.fillConvexPoly(frame, np.array(convex_hull_vertices), (255, 255, 255))
return frame