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from lib.kits.basic import *
import cv2
import imageio
from lib.utils.data import to_numpy
from lib.utils.vis import ColorPalette
def annotate_img(
img : np.ndarray,
text : str,
pos : Union[str, Tuple[int, int]] = 'bl',
):
'''
Annotate the image with the given text.
### Args
- img: np.ndarray, (H, W, 3)
- text: str
- pos: str or tuple(int, int), default 'bl'
- If str, one of ['tl', 'bl'].
- If tuple, the position of the text.
### Returns
- np.ndarray, (H, W, 3)
- The annotated image.
'''
assert len(img.shape) == 3, 'img must have 3 dimensions.'
return annotate_video(frames=img[None], text=text, pos=pos)[0]
def annotate_video(
frames : np.ndarray,
text : str,
pos : Union[str, Tuple[int, int]] = 'bl',
alpha : float = 0.75,
):
'''
Annotate the video frames with the given text.
### Args
- frames: np.ndarray, (L, H, W, 3)
- text: str
- pos: str or tuple(int, int), default 'bl'
- If str, one of ['tl', 'bl'].
- If tuple, the position of the text.
- alpha: float, default 0.5
- The transparency of the text.
### Returns
- np.ndarray, (L, H, W, 3)
- The annotated video.
'''
assert len(frames.shape) == 4, 'frames must have 4 dimensions.'
frames = frames.copy()
L, H, W = frames.shape[:3]
if isinstance(pos, str):
if pos == 'tl':
offset = (int(0.1 * W), int(0.1 * H))
elif pos == 'bl':
offset = (int(0.1 * W), int(0.9 * H))
else:
raise ValueError(f'Invalid position: {pos}')
else:
offset = pos
for i, frame in enumerate(frames):
overlay = frame.copy()
_put_text(overlay, text, offset)
frames[i] = cv2.addWeighted(overlay, alpha, frame, 1 - alpha, 0)
return frames
def draw_bbx_on_img(
img : np.ndarray,
lurb : np.ndarray,
color : str = 'red',
):
'''
Draw the bounding box on the image.
### Args
- img: np.ndarray, (H, W, 3)
- lurb: np.ndarray, (4,)
- The bounding box in the format of left, up, right, bottom.
- color: str, default 'red'
### Returns
- np.ndarray, (H, W, 3)
- The image with the bounding box.
'''
assert len(img.shape) == 3, 'img must have 3 dimensions.'
img = img.copy()
l, u, r, b = lurb.astype(int)
color_rgb_int8 = ColorPalette.presets_int8[color]
cv2.rectangle(img, (l, u), (r, b), color_rgb_int8, 3)
return img
def draw_bbx_on_video(
frames : np.ndarray,
lurbs : np.ndarray,
color : str = 'red',
):
'''
Draw the bounding box on the video frames.
### Args
- frames: np.ndarray, (L, H, W, 3)
- lurbs: np.ndarray, (L, 4,)
- The bounding box in the format of left, up, right, bottom.
- color: str, default 'red'
### Returns
- np.ndarray, (L, H, W, 3)
- The video with the bounding box.
'''
assert len(frames.shape) == 4, 'frames must have 4 dimensions.'
frames = frames.copy()
for i, frame in enumerate(frames):
frames[i] = draw_bbx_on_img(frame, lurbs[i], color)
return frames
def draw_kp2d_on_img(
img : np.ndarray,
kp2d : Union[np.ndarray, torch.Tensor],
links : list = [],
link_colors : list = [],
show_conf : bool = False,
show_idx : bool = False,
):
'''
Draw the 2d keypoints (and connection lines if exists) on the image.
### Args
- img: np.ndarray, (H, W, 3)
- The image.
- kp2d: np.ndarray or torch.Tensor, (N, 2) or (N, 3)
- The 2d keypoints without/with confidence.
- links: list of [int, int] or (int, int), default []
- The connections between keypoints. Each element is a tuple of two indices.
- If empty, only keypoints will be drawn.
- link_colors: list of [int, int, int] or (int, int, int), default []
- The colors of the connections.
- If empty, the connections will be drawn in white.
- show_conf: bool, default False
- Whether to show the confidence of keypoints.
- show_idx: bool, default False
- Whether to show the index of keypoints.
### Returns
- img: np.ndarray, (H, W, 3)
- The image with skeleton.
'''
img = img.copy()
kp2d = to_numpy(kp2d) # (N, 2) or (N, 3)
assert len(img.shape) == 3, f'`img`\'s shape should be (H, W, 3) but got {img.shape}'
assert len(kp2d.shape) == 2, f'`kp2d`\'s shape should be (N, 2) or (N, 3) but got {kp2d.shape}'
if kp2d.shape[1] == 2:
kp2d = np.concatenate([kp2d, np.ones((kp2d.shape[0], 1))], axis=-1) # (N, 3)
kp_has_drawn = [False] * kp2d.shape[0]
# Draw connections.
for lid, link in enumerate(links):
# Skip links related to impossible keypoints.
if kp2d[link[0], 2] < 0.5 or kp2d[link[1], 2] < 0.5:
continue
pt1 = tuple(kp2d[link[0], :2].astype(int))
pt2 = tuple(kp2d[link[1], :2].astype(int))
color = (255, 255, 255) if len(link_colors) == 0 else tuple(link_colors[lid])
cv2.line(img, pt1, pt2, color, 2)
if not kp_has_drawn[link[0]]:
cv2.circle(img, pt1, 3, color, -1)
if not kp_has_drawn[link[1]]:
cv2.circle(img, pt2, 3, color, -1)
kp_has_drawn[link[0]] = kp_has_drawn[link[1]] = True
# Draw keypoints and annotate the confidence.
for i, kp in enumerate(kp2d):
conf = kp[2]
pos = tuple(kp[:2].astype(int))
if not kp_has_drawn[i]:
cv2.circle(img, pos, 4, (255, 255, 255), -1)
cv2.circle(img, pos, 2, ( 0, 255, 0), -1)
kp_has_drawn[i] = True
if show_conf:
_put_text(img, f'{conf:.2f}', pos)
if show_idx:
if i >= 40:
continue
_put_text(img, f'{i}', pos, scale=0.03)
return img
# ====== Internal Utils ======
def _put_text(
img : np.ndarray,
text : str,
pos : Tuple[int, int],
scale : float = 0.05,
color_inside : Tuple[int, int, int] = ColorPalette.presets_int8['black'],
color_stroke : Tuple[int, int, int] = ColorPalette.presets_int8['white'],
**kwargs
):
fontFace = cv2.FONT_HERSHEY_SIMPLEX
if 'fontFace' in kwargs:
fontFace = kwargs['fontFace']
kwargs.pop('fontFace')
H, W = img.shape[:2]
# https://stackoverflow.com/a/55772676/22331129
font_scale = scale * min(H, W) / 25 * 1.5
thickness_inside = max(int(font_scale), 1)
thickness_stroke = max(int(font_scale * 6), 6)
# Deal with the multi-line text.
((fw, fh), baseline) = cv2.getTextSize(
text = text,
fontFace = fontFace,
fontScale = font_scale,
thickness = thickness_stroke,
) # https://stackoverflow.com/questions/73664883/opencv-python-draw-text-with-fontsize-in-pixels
lines = text.split('\n')
line_height = baseline + fh
for i, line in enumerate(lines):
pos_ = (pos[0], pos[1] + line_height * i)
cv2.putText(img, line, pos_, fontFace, font_scale, color_stroke, thickness_stroke)
cv2.putText(img, line, pos_, fontFace, font_scale, color_inside, thickness_inside) |