def publishCharacterImage(self):
from PIL import Image, ImageDraw, ImageFilter
# Publish Image with label
img = self.img
for x, y, label in zip(self.person_x, self.person_y, self.labels):
# Draw character image --->
os.chdir(self.PICTURE_URL)
char = ch.CHARACTER_PICTURE[int(label)]
# Load and resize
src = pil_image.cv2pil(img)
forward = Image.open( char["filename"])
h, w = forward.size
forward = forward.resize((int(h*char["size"]), int(w*char["size"])))
# For convert
src = src.convert('RGBA')
# Paste
c = Image.new('RGBA', src.size, (255, 255, 255, 0))
#src.paste(forward, ( char["x"], char["y"]))
#c.paste(forward, ( char["x"] + x, char["y"] + y), forward)
c.paste(forward, ( char["x"] + x - int(char["size"]*h/2), char["y"] + y - int(char["size"]*w/2)), forward)
result = Image.alpha_composite(src, c)
result.save('tmp.jpg', quality=95)
img = cv.imread('tmp.jpg')
# Write label name to img
cv.putText(img, ch.CHARACTER_NAME[int(label)], (x-50,y), cv.FONT_HERSHEY_SIMPLEX, 0.9, (0,0,150), 2, cv.LINE_AA)
msg = self.bridge.cv2_to_imgmsg(img, encoding="rgb8")
self.image_pub.publish(msg)
def resize_keep_ratio(self, img, width, height, fill_color=(0, 0, 0, 0)):
#======= Make sure image is smaller than background =======
h, w, channel = img.shape
h_ratio = float(float(height) / float(h))
w_ratio = float(float(width) / float(w))
#if h_ratio <= 1 or w_ratio <= 1:
ratio = h_ratio
if h_ratio > w_ratio:
ratio = w_ratio
img = cv2.resize(img, (int(ratio * w), int(ratio * h)))
#======== Paste image to background =======
im = Image.fromarray(np.uint8(img))
x, y = im.size
new_im = Image.new('RGBA', (width, height), fill_color)
new_im.paste(im, ((width - x) / 2, (height - y) / 2))
return np.asarray(new_im)
def print_road_map(image, left_line, right_line):
""" print simple road map """
img = cv2.imread('images/top_view_car.png', -1)
img = cv2.resize(img, (120, 246))
rows, cols = image.shape[:2]
window_img = np.zeros_like(image)
window_margin = left_line.window_margin
left_plotx, right_plotx = left_line.allx, right_line.allx
ploty = left_line.ally
lane_width = right_line.startx - left_line.startx
lane_center = (right_line.startx + left_line.startx) / 2
lane_offset = cols / 2 - (2 * left_line.startx + lane_width) / 2
car_offset = int(lane_center - 360)
# Generate a polygon to illustrate the search window area
# And recast the x and y points into usable format for cv2.fillPoly()
left_pts_l = np.array([
np.transpose(
np.vstack([
right_plotx - lane_width + lane_offset - window_margin / 4,
ploty
]))
])
left_pts_r = np.array([
np.flipud(
np.transpose(
np.vstack([
right_plotx - lane_width + lane_offset + window_margin / 4,
ploty
])))
])
left_pts = np.hstack((left_pts_l, left_pts_r))
right_pts_l = np.array([
np.transpose(
np.vstack([right_plotx + lane_offset - window_margin / 4, ploty]))
])
right_pts_r = np.array([
np.flipud(
np.transpose(
np.vstack(
[right_plotx + lane_offset + window_margin / 4, ploty])))
])
right_pts = np.hstack((right_pts_l, right_pts_r))
# Draw the lane onto the warped blank image
cv2.fillPoly(window_img, np.int_([left_pts]), (140, 0, 170))
cv2.fillPoly(window_img, np.int_([right_pts]), (140, 0, 170))
# Recast the x and y points into usable format for cv2.fillPoly()
pts_left = np.array([
np.transpose(
np.vstack([
right_plotx - lane_width + lane_offset + window_margin / 4,
ploty
]))
])
pts_right = np.array([
np.flipud(
np.transpose(
np.vstack(
[right_plotx + lane_offset - window_margin / 4, ploty])))
])
pts = np.hstack((pts_left, pts_right))
# Draw the lane onto the warped blank image
cv2.fillPoly(window_img, np.int_([pts]), (0, 160, 0))
#window_img[10:133,300:360] = img
road_map = Image.new('RGBA', image.shape[:2], (0, 0, 0, 0))
window_img = Image.fromarray(window_img)
img = Image.fromarray(img)
road_map.paste(window_img, (0, 0))
road_map.paste(img, (300 - car_offset, 590), mask=img)
road_map = np.array(road_map)
road_map = cv2.resize(road_map, (95, 95))
road_map = cv2.cvtColor(road_map, cv2.COLOR_BGRA2BGR)
return road_map
