# Copyright (c) OpenMMLab. All rights reserved.
# Adapt from https://github.com/open-mmlab/mmpose/blob/master/mmpose/core/visualization/image.py
import math
import os
from os.path import dirname as opd
import cv2
import mmcv
import numpy as np
from mmcv.utils.misc import deprecated_api_warning
from PIL import Image, ImageDraw, ImageFont
from easycv.framework.errors import FileNotFoundError
[docs]def get_font_path():
root_path = opd(opd(opd(os.path.realpath(__file__))))
# find in whl
find_path_whl = os.path.join(root_path, 'resource/simhei.ttf')
# find in source code
find_path_source = os.path.join(opd(root_path), 'resource/simhei.ttf')
if os.path.exists(find_path_whl):
return find_path_whl
elif os.path.exists(find_path_source):
return find_path_source
else:
raise FileNotFoundError('Not find font file both in %s and %s' %
(find_path_whl, find_path_source))
_FONT_PATH = get_font_path()
[docs]def put_text(img, xy, text, fill, size=20):
"""support chinese text
"""
img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
draw = ImageDraw.Draw(img)
fontText = ImageFont.truetype(_FONT_PATH, size=size, encoding='utf-8')
draw.text(xy, text, fill=fill, font=fontText)
img = cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)
return img
[docs]def imshow_label(img,
labels,
text_color='blue',
font_size=20,
thickness=1,
font_scale=0.5,
intervel=5,
show=True,
win_name='',
wait_time=0,
out_file=None):
"""Draw images with labels on an image.
Args:
img (str or ndarray): The image to be displayed.
labels (str or list[str]): labels of each image.
text_color (str or tuple or :obj:`Color`): Color of texts.
font_size (int): Size of font.
thickness (int): Thickness of lines.
font_scale (float): Font scales of texts.
intervel（int): interval pixels between multiple labels
show (bool): Whether to show the image.
win_name (str): The window name.
wait_time (int): Value of waitKey param.
out_file (str, optional): The filename to write the image.
Returns:
ndarray: The image with bboxes drawn on it.
"""
img = mmcv.imread(img)
img = np.ascontiguousarray(img)
labels = [labels] if isinstance(labels, str) else labels
cur_height = 0
for label in labels:
# roughly estimate the proper font size
text_size, text_baseline = cv2.getTextSize(label,
cv2.FONT_HERSHEY_DUPLEX,
font_scale, thickness)
org = (text_baseline + text_size[1],
text_baseline + text_size[1] + cur_height)
# support chinese text
# TODO: Unify the font of cv2 and PIL, and auto get font_size according to the font_scale
img = put_text(img, org, text=label, fill=text_color, size=font_size)
# cv2.putText(img, label, org, cv2.FONT_HERSHEY_DUPLEX, font_scale,
# mmcv.color_val(text_color), thickness)
cur_height += text_baseline + text_size[1] + intervel
if show:
mmcv.imshow(img, win_name, wait_time)
if out_file is not None:
mmcv.imwrite(img, out_file)
return img
[docs]def imshow_bboxes(img,
bboxes,
labels=None,
colors='green',
text_color='white',
font_size=20,
thickness=1,
font_scale=0.5,
show=True,
win_name='',
wait_time=0,
out_file=None):
"""Draw bboxes with labels (optional) on an image. This is a wrapper of
mmcv.imshow_bboxes.
Args:
img (str or ndarray): The image to be displayed.
bboxes (ndarray): ndarray of shape (k, 4), each row is a bbox in
format [x1, y1, x2, y2].
labels (str or list[str], optional): labels of each bbox.
colors (list[str or tuple or :obj:`Color`]): A list of colors.
text_color (str or tuple or :obj:`Color`): Color of texts.
font_size (int): Size of font.
thickness (int): Thickness of lines.
font_scale (float): Font scales of texts.
show (bool): Whether to show the image.
win_name (str): The window name.
wait_time (int): Value of waitKey param.
out_file (str, optional): The filename to write the image.
Returns:
ndarray: The image with bboxes drawn on it.
"""
# adapt to mmcv.imshow_bboxes input format
bboxes = np.split(
bboxes, bboxes.shape[0], axis=0) if bboxes.shape[0] > 0 else []
if not isinstance(colors, list):
colors = [colors for _ in range(len(bboxes))]
colors = [mmcv.color_val(c) for c in colors]
assert len(bboxes) == len(colors)
img = mmcv.imshow_bboxes(
img,
bboxes,
colors,
top_k=-1,
thickness=thickness,
show=False,
out_file=None)
if labels is not None:
assert len(labels) == len(bboxes)
for bbox, label, color in zip(bboxes, labels, colors):
label = str(label)
bbox_int = bbox[0, :4].astype(np.int32)
# roughly estimate the proper font size
text_size, text_baseline = cv2.getTextSize(label,
cv2.FONT_HERSHEY_DUPLEX,
font_scale, thickness)
text_x1 = bbox_int[0]
text_y1 = max(0, bbox_int[1] - text_size[1] - text_baseline)
text_x2 = bbox_int[0] + text_size[0]
text_y2 = text_y1 + text_size[1] + text_baseline
cv2.rectangle(img, (text_x1, text_y1), (text_x2, text_y2), color,
cv2.FILLED)
# cv2.putText(img, label, (text_x1, text_y2 - text_baseline),
# cv2.FONT_HERSHEY_DUPLEX, font_scale,
# mmcv.color_val(text_color), thickness)
# support chinese text
# TODO: Unify the font of cv2 and PIL, and auto get font_size according to the font_scale
img = put_text(
img, (text_x1, text_y1),
text=label,
fill=text_color,
size=font_size)
if show:
mmcv.imshow(img, win_name, wait_time)
if out_file is not None:
mmcv.imwrite(img, out_file)
return img
[docs]@deprecated_api_warning({'pose_limb_color': 'pose_link_color'})
def imshow_keypoints(img,
pose_result,
skeleton=None,
kpt_score_thr=0.3,
pose_kpt_color=None,
pose_link_color=None,
radius=4,
thickness=1,
show_keypoint_weight=False):
"""Draw keypoints and links on an image.
Args:
img (str or Tensor): The image to draw poses on. If an image array
is given, id will be modified in-place.
pose_result (list[kpts]): The poses to draw. Each element kpts is
a set of K keypoints as an Kx3 numpy.ndarray, where each
keypoint is represented as x, y, score.
kpt_score_thr (float, optional): Minimum score of keypoints
to be shown. Default: 0.3.
pose_kpt_color (np.array[Nx3]`): Color of N keypoints. If None,
the keypoint will not be drawn.
pose_link_color (np.array[Mx3]): Color of M links. If None, the
links will not be drawn.
thickness (int): Thickness of lines.
"""
img = mmcv.imread(img)
img_h, img_w, _ = img.shape
for kpts in pose_result:
kpts = np.array(kpts, copy=False)
# draw each point on image
if pose_kpt_color is not None:
assert len(pose_kpt_color) == len(kpts)
for kid, kpt in enumerate(kpts):
x_coord, y_coord, kpt_score = int(kpt[0]), int(kpt[1]), kpt[2]
if kpt_score > kpt_score_thr:
if show_keypoint_weight:
img_copy = img.copy()
r, g, b = pose_kpt_color[kid]
cv2.circle(img_copy, (int(x_coord), int(y_coord)),
radius, (int(r), int(g), int(b)), -1)
transparency = max(0, min(1, kpt_score))
cv2.addWeighted(
img_copy,
transparency,
img,
1 - transparency,
0,
dst=img)
else:
r, g, b = pose_kpt_color[kid]
cv2.circle(img, (int(x_coord), int(y_coord)), radius,
(int(r), int(g), int(b)), -1)
# draw links
if skeleton is not None and pose_link_color is not None:
assert len(pose_link_color) == len(skeleton)
for sk_id, sk in enumerate(skeleton):
pos1 = (int(kpts[sk[0], 0]), int(kpts[sk[0], 1]))
pos2 = (int(kpts[sk[1], 0]), int(kpts[sk[1], 1]))
if (pos1[0] > 0 and pos1[0] < img_w and pos1[1] > 0
and pos1[1] < img_h and pos2[0] > 0 and pos2[0] < img_w
and pos2[1] > 0 and pos2[1] < img_h
and kpts[sk[0], 2] > kpt_score_thr
and kpts[sk[1], 2] > kpt_score_thr):
r, g, b = pose_link_color[sk_id]
if show_keypoint_weight:
img_copy = img.copy()
X = (pos1[0], pos2[0])
Y = (pos1[1], pos2[1])
mX = np.mean(X)
mY = np.mean(Y)
length = ((Y[0] - Y[1])**2 + (X[0] - X[1])**2)**0.5
angle = math.degrees(
math.atan2(Y[0] - Y[1], X[0] - X[1]))
stickwidth = 2
polygon = cv2.ellipse2Poly(
(int(mX), int(mY)),
(int(length / 2), int(stickwidth)), int(angle), 0,
360, 1)
cv2.fillConvexPoly(img_copy, polygon,
(int(r), int(g), int(b)))
transparency = max(
0, min(1, 0.5 * (kpts[sk[0], 2] + kpts[sk[1], 2])))
cv2.addWeighted(
img_copy,
transparency,
img,
1 - transparency,
0,
dst=img)
else:
cv2.line(
img,
pos1,
pos2, (int(r), int(g), int(b)),
thickness=thickness)
return img