Python cv2.CV_AA Examples
The following are 30
code examples of cv2.CV_AA().
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Example #1
| Source File: sunrgbd_utils.py From H3DNet with MIT License | 6 votes |
|
def draw_projected_box3d(image, qs, color=(255,255,255), thickness=2):
''' Draw 3d bounding box in image
qs: (8,2) array of vertices for the 3d box in following order:
1 -------- 0
/| /|
2 -------- 3 .
| | | |
. 5 -------- 4
|/ |/
6 -------- 7
'''
qs = qs.astype(np.int32)
for k in range(0,4):
#http://docs.enthought.com/mayavi/mayavi/auto/mlab_helper_functions.html
i,j=k,(k+1)%4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA) # use LINE_AA for opencv3
i,j=k+4,(k+1)%4 + 4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
i,j=k,k+4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
return image
Example #2
| Source File: utils.py From reading-frustum-pointnets-code with Apache License 2.0 | 6 votes |
|
def draw_projected_box3d(image, qs, color=(255,255,255), thickness=2):
''' Draw 3d bounding box in image
qs: (8,2) array of vertices for the 3d box in following order:
1 -------- 0
/| /|
2 -------- 3 .
| | | |
. 5 -------- 4
|/ |/
6 -------- 7
'''
qs = qs.astype(np.int32)
for k in range(0,4):
#http://docs.enthought.com/mayavi/mayavi/auto/mlab_helper_functions.html
i,j=k,(k+1)%4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA) # use LINE_AA for opencv3
i,j=k+4,(k+1)%4 + 4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
i,j=k,k+4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
return image
Example #3
| Source File: kitti_util.py From reading-frustum-pointnets-code with Apache License 2.0 | 6 votes |
|
def draw_projected_box3d(image, qs, color=(255,255,255), thickness=2):
''' Draw 3d bounding box in image
qs: (8,3) array of vertices for the 3d box in following order:
1 -------- 0
/| /|
2 -------- 3 .
| | | |
. 5 -------- 4
|/ |/
6 -------- 7
'''
qs = qs.astype(np.int32)
for k in range(0,4):
# Ref: http://docs.enthought.com/mayavi/mayavi/auto/mlab_helper_functions.html
i,j=k,(k+1)%4
# use LINE_AA for opencv3
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
i,j=k+4,(k+1)%4 + 4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
i,j=k,k+4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
return image
Example #4
| Source File: kitti_util.py From frustum-pointnets with Apache License 2.0 | 6 votes |
|
def draw_projected_box3d(image, qs, color=(255,255,255), thickness=2):
''' Draw 3d bounding box in image
qs: (8,3) array of vertices for the 3d box in following order:
1 -------- 0
/| /|
2 -------- 3 .
| | | |
. 5 -------- 4
|/ |/
6 -------- 7
'''
qs = qs.astype(np.int32)
for k in range(0,4):
# Ref: http://docs.enthought.com/mayavi/mayavi/auto/mlab_helper_functions.html
i,j=k,(k+1)%4
# use LINE_AA for opencv3
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
i,j=k+4,(k+1)%4 + 4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
i,j=k,k+4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
return image
Example #5
| Source File: test.py From yolo_v1_tensorflow_guiyu with MIT License | 6 votes |
|
def draw_result(self, img, result): #输出结果
print("hell")
print(len(result))
for i in range(len(result)):
x = int(result[i][1])
y = int(result[i][2])
w = int(result[i][3] / 2)
h = int(result[i][4] / 2)
cv2.rectangle(img, (x - w, y - h), (x + w, y + h), (0, 255, 0), 2)
cv2.rectangle(img, (x - w, y - h - 20),
(x + w, y - h), (125, 125, 125), -1)
lineType = cv2.LINE_AA if cv2.__version__ > '3' else cv2.CV_AA
cv2.putText(
img, result[i][0] + ' : %.2f' % result[i][5],
(x - w + 5, y - h - 7), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
(0, 0, 0), 1, lineType)
Example #6
| Source File: utils.py From frustum-pointnets with Apache License 2.0 | 6 votes |
|
def draw_projected_box3d(image, qs, color=(255,255,255), thickness=2):
''' Draw 3d bounding box in image
qs: (8,2) array of vertices for the 3d box in following order:
1 -------- 0
/| /|
2 -------- 3 .
| | | |
. 5 -------- 4
|/ |/
6 -------- 7
'''
qs = qs.astype(np.int32)
for k in range(0,4):
#http://docs.enthought.com/mayavi/mayavi/auto/mlab_helper_functions.html
i,j=k,(k+1)%4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA) # use LINE_AA for opencv3
i,j=k+4,(k+1)%4 + 4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
i,j=k,k+4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
return image
Example #7
| Source File: vis.py From DetectAndTrack with Apache License 2.0 | 6 votes |
|
def vis_mask(img, mask, col, alpha=0.4, show_border=True, border_thick=1):
"""Visualizes a single binary mask."""
img = img.astype(np.float32)
idx = np.nonzero(mask)
img[idx[0], idx[1], :] *= 1.0 - alpha
img[idx[0], idx[1], :] += alpha * col
if show_border:
contours, _ = cv2.findContours(
mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(img, contours, -1, _WHITE, border_thick,
cv2.CV_AA if cv2.__version__.startswith('2') else
cv2.LINE_AA)
return img.astype(np.uint8)
Example #8
| Source File: vis.py From DetectAndTrack with Apache License 2.0 | 6 votes |
|
def vis_class(img, pos, class_str, font_scale=0.35):
"""Visualizes the class."""
x0, y0 = int(pos[0]), int(pos[1])
# Compute text size.
txt = class_str
font = cv2.FONT_HERSHEY_SIMPLEX
((txt_w, txt_h), _) = cv2.getTextSize(txt, font, font_scale, 1)
# Place text background.
back_tl = x0, y0 - int(1.3 * txt_h)
back_br = x0 + txt_w, y0
cv2.rectangle(img, back_tl, back_br, _GREEN, -1)
# Show text.
txt_tl = x0, y0 - int(0.3 * txt_h)
cv2.putText(img, txt, txt_tl, font, font_scale, _GRAY,
lineType=cv2.CV_AA if cv2.__version__.startswith('2') else
cv2.LINE_AA)
return img
Example #9
| Source File: sunrgbd_utils.py From votenet with MIT License | 6 votes |
|
def draw_projected_box3d(image, qs, color=(255,255,255), thickness=2):
''' Draw 3d bounding box in image
qs: (8,2) array of vertices for the 3d box in following order:
1 -------- 0
/| /|
2 -------- 3 .
| | | |
. 5 -------- 4
|/ |/
6 -------- 7
'''
qs = qs.astype(np.int32)
for k in range(0,4):
#http://docs.enthought.com/mayavi/mayavi/auto/mlab_helper_functions.html
i,j=k,(k+1)%4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA) # use LINE_AA for opencv3
i,j=k+4,(k+1)%4 + 4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
i,j=k,k+4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
return image
Example #10
| Source File: viz.py From Object_Detection_Tracking with Apache License 2.0 | 6 votes |
|
def draw_mask(im, mask, alpha=0.5, color=None, show_border=True,border_thick=1):
"""
Overlay a mask on top of the image.
Args:
im: a 3-channel uint8 image in BGR
mask: a binary 1-channel image of the same size
color: if None, will choose automatically
"""
if color is None:
color = PALETTE_RGB[np.random.choice(len(PALETTE_RGB))][::-1]
im = np.where(np.squeeze(np.repeat((mask > 0)[:, :, None], 3, axis=2)),
im * (1 - alpha) + color * alpha, im)
if show_border:
if cv2.__version__.startswith("2"):
contours, _ = cv2.findContours(mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
else: # cv 3
_,contours, _ = cv2.findContours(mask.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(im, contours, -1, (255,255,255), border_thick, lineType=cv2.CV_AA)
im = im.astype('uint8')
return im
Example #11
| Source File: kitti_util.py From Geo-CNN with Apache License 2.0 | 6 votes |
|
def draw_projected_box3d(image, qs, color=(255,255,255), thickness=2):
''' Draw 3d bounding box in image
qs: (8,3) array of vertices for the 3d box in following order:
1 -------- 0
/| /|
2 -------- 3 .
| | | |
. 5 -------- 4
|/ |/
6 -------- 7
'''
qs = qs.astype(np.int32)
for k in range(0,4):
# Ref: http://docs.enthought.com/mayavi/mayavi/auto/mlab_helper_functions.html
i,j=k,(k+1)%4
# use LINE_AA for opencv3
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
i,j=k+4,(k+1)%4 + 4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
i,j=k,k+4
cv2.line(image, (qs[i,0],qs[i,1]), (qs[j,0],qs[j,1]), color, thickness, cv2.CV_AA)
return image
Example #12
| Source File: common.py From ImageAnalysis with MIT License | 5 votes |
|
def draw_str(dst, pt, s):
x = pt[0]
y = pt[1]
cv2.putText(dst, s, (x+1, y+1), cv2.FONT_HERSHEY_PLAIN, 1.0, (0, 0, 0), thickness = 2, lineType=cv2.CV_AA)
cv2.putText(dst, s, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.0, (255, 255, 255), lineType=cv2.CV_AA)
Example #13
| Source File: deconvolution.py From PyCV-time with MIT License | 5 votes |
|
def defocus_kernel(d, sz=65):
kern = np.zeros((sz, sz), np.uint8)
cv2.circle(kern, (sz, sz), d, 255, -1, cv2.CV_AA, shift=1)
kern = np.float32(kern) / 255.0
return kern
Example #14
| Source File: gaussian_mix.py From PyCV-time with MIT License | 5 votes |
|
def draw_gaussain(img, mean, cov, color):
x, y = np.int32(mean)
w, u, vt = cv2.SVDecomp(cov)
ang = np.arctan2(u[1, 0], u[0, 0])*(180/np.pi)
s1, s2 = np.sqrt(w)*3.0
cv2.ellipse(img, (x, y), (s1, s2), ang, 0, 360, color, 1, cv2.CV_AA)
Example #15
| Source File: video.py From PyCV-time with MIT License | 5 votes |
|
def draw_quads(self, img, quads, color = (0, 255, 0)):
img_quads = cv2.projectPoints(quads.reshape(-1, 3), self.rvec, self.tvec, self.K, self.dist_coef) [0]
img_quads.shape = quads.shape[:2] + (2,)
for q in img_quads:
cv2.fillConvexPoly(img, np.int32(q*4), color, cv2.CV_AA, shift=2)
Example #16
| Source File: contours.py From PyCV-time with MIT License | 5 votes |
|
def update(levels):
vis = np.zeros((h, w, 3), np.uint8)
levels = levels - 3
cv2.drawContours( vis, contours, (-1, 3)[levels <= 0], (128,255,255),
3, cv2.CV_AA, hierarchy, abs(levels) )
cv2.imshow('contours', vis)
Example #17
| Source File: test.py From yolo_tensorflow with MIT License | 5 votes |
|
def draw_result(self, img, result):
for i in range(len(result)):
x = int(result[i][1])
y = int(result[i][2])
w = int(result[i][3] / 2)
h = int(result[i][4] / 2)
cv2.rectangle(img, (x - w, y - h), (x + w, y + h), (0, 255, 0), 2)
cv2.rectangle(img, (x - w, y - h - 20),
(x + w, y - h), (125, 125, 125), -1)
lineType = cv2.LINE_AA if cv2.__version__ > '3' else cv2.CV_AA
cv2.putText(
img, result[i][0] + ' : %.2f' % result[i][5],
(x - w + 5, y - h - 7), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
(0, 0, 0), 1, lineType)
Example #18
| Source File: main_frame.py From Rule-based_Expert_System with GNU General Public License v2.0 | 5 votes |
|
def draw_lines(image, facts, contour_num):
for i in range(contour_num):
for fact in facts['Contour' + str(i)]:
for line in fact.about:
cv2.line(image, line.point1, line.point2, (0, 255, 0), 2, cv2.CV_AA)
Example #19
| Source File: tube_automask_monitor.py From ethoscope with GNU General Public License v3.0 | 5 votes |
|
def draw_rois(im, all_rois):
for roi in all_rois:
x,y = roi.offset
y += roi.rectangle[3]/2
x += roi.rectangle[2]/2
cv2.putText(im, str(roi.idx), (x,y), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (255,255,0))
black_colour,roi_colour = (0, 0,0), (0, 255,0)
cv2.drawContours(im,[roi.polygon],-1, black_colour, 3, cv2.CV_AA)
cv2.drawContours(im,[roi.polygon],-1, roi_colour, 1, cv2.CV_AA)
Example #20
| Source File: automask_monitor.py From ethoscope with GNU General Public License v3.0 | 5 votes |
|
def draw_rois(im, all_rois):
for roi in all_rois:
x,y = roi.offset
y += roi.rectangle[3]/2
x += roi.rectangle[2]/2
cv2.putText(im, str(roi.idx), (x,y), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (255,255,0))
black_colour,roi_colour = (0, 0,0), (0, 255,0)
cv2.drawContours(im,[roi.polygon],-1, black_colour, 3, cv2.CV_AA)
cv2.drawContours(im,[roi.polygon],-1, roi_colour, 1, cv2.CV_AA)
Example #21
| Source File: target_detector.py From ethoscope with GNU General Public License v3.0 | 5 votes |
|
def draw_rois(im, all_rois):
for roi in all_rois:
x,y = roi.offset
y += roi.rectangle[3]/2
x += roi.rectangle[2]/2
cv2.putText(im, str(roi.idx), (x,y), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (255,255,0))
black_colour,roi_colour = (0, 0,0), (0, 255,0)
cv2.drawContours(im,[roi.polygon],-1, black_colour, 3, cv2.CV_AA)
cv2.drawContours(im,[roi.polygon],-1, roi_colour, 1, cv2.CV_AA)
Example #22
| Source File: kalman_1.py From Python-Code with MIT License | 5 votes |
|
def drawCross(img, center, r, g, b):
'''
Draws a cross a the specified X,Y coordinates with color RGB
'''
d = 5
t = 2
color = (r, g, b)
ctrx = center[0]
ctry = center[1]
cv2.line(img, (ctrx - d, ctry - d), (ctrx + d, ctry + d), color, t, cv2.CV_AA)
cv2.line(img, (ctrx + d, ctry - d), (ctrx - d, ctry + d), color, t, cv2.CV_AA)
Example #23
| Source File: main.py From YOLO-Object-Detection-Tensorflow with MIT License | 5 votes |
|
def draw_result(img, result):
for i in range(len(result)):
x = int(result[i][1])
y = int(result[i][2])
w = int(result[i][3] / 2)
h = int(result[i][4] / 2)
cv2.rectangle(img, (x - w, y - h), (x + w, y + h), (0, 255, 0), 2)
cv2.rectangle(img, (x - w, y - h - 20), (x + w, y - h), (125, 125, 125), -1)
cv2.putText(img, result[i][0] + ' : %.2f' % result[i][5], (x - w + 5, y - h - 7), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 1, cv2.CV_AA)
Example #24
| Source File: aircv.py From Airtest with Apache License 2.0 | 5 votes |
|
def mark_point(img, point, circle=False, color=100, radius=20):
""" 调试用的: 标记一个点 """
x, y = point
# cv2.rectangle(img, (x, y), (x+10, y+10), 255, 1, lineType=cv2.CV_AA)
if circle:
cv2.circle(img, (x, y), radius, 255, thickness=2)
cv2.line(img, (x - radius, y), (x + radius, y), color) # x line
cv2.line(img, (x, y - radius), (x, y + radius), color) # y line
return img
Example #25
| Source File: tc_common.py From rpitelecine with BSD 3-Clause "New" or "Revised" License | 5 votes |
|
def display_shadow_text(img,x,y,text):
"""
Displays with a grey shadow at point x,y
"""
text_color = (255,255,255) #color as (B,G,R)
text_shadow = (0,0,0)
text_pos = (x,y)
shadow_pos = (x+1,y+1)
cv2.putText(img, text, shadow_pos, cv2.FONT_HERSHEY_PLAIN, 1.25, text_shadow, thickness=1, lineType=cv2.CV_AA)
cv2.putText(img, text, text_pos, cv2.FONT_HERSHEY_PLAIN, 1.25, text_color, thickness=1, lineType=cv2.CV_AA)
return img
Example #26
| Source File: hostage.py From MADRL with MIT License | 4 votes |
|
def render(self, screen_size=800, rate=10):
import cv2
img = np.empty((screen_size, screen_size, 3), dtype=np.uint8)
img[...] = 255
# Stationary objects
if not self.is_gate_open:
color = (128, 128, 200)
cv2.line(img, tuple(np.array([0 * screen_size, 0.5 * screen_size]).astype(int)),
tuple(np.array([1 * screen_size, 0.5 * screen_size]).astype(int)), color, 1,
lineType=cv2.CV_AA)
keyx_2 = np.squeeze(self.key_loc)
assert keyx_2.shape == (2,)
kcolor = (0, 0, 255)
cv2.circle(img, tuple((keyx_2 * screen_size).astype(int)),
int(self.radius * screen_size), kcolor, -1, lineType=cv2.CV_AA)
for ibomb, bombx_2 in enumerate(self.bomb_loc):
assert bombx_2.shape == (2,)
color = (0, 0, 255)
cv2.circle(img, tuple((bombx_2 * screen_size).astype(int)),
int(self.bomb_radius * screen_size), color, -1, lineType=cv2.CV_AA)
for hostage in np.asarray(self._hostages)[~self.curr_host_saved_mask]:
color = (255, 120, 0)
cv2.circle(img, tuple((hostage.position * screen_size).astype(int)),
int(hostage._radius * screen_size), color, -1, lineType=cv2.CV_AA)
for criminal in self._criminals:
color = (50, 50, 200)
cv2.circle(img, tuple((criminal.position * screen_size).astype(int)),
int(criminal._radius * screen_size), color, -1, lineType=cv2.CV_AA)
for rescuer in self._rescuers:
for k in range(rescuer._n_sensors):
color = (0, 0, 0)
cv2.line(img, tuple((rescuer.position * screen_size).astype(int)),
tuple(((rescuer.position + rescuer._sensor_range * rescuer.sensors[k]) *
screen_size).astype(int)), color, 1, lineType=cv2.CV_AA)
cv2.circle(img, tuple((rescuer.position * screen_size).astype(int)),
int(rescuer._radius * screen_size), (255, 0, 0), -1, lineType=cv2.CV_AA)
opacity = 0.4
bg = np.ones((screen_size, screen_size, 3), dtype=np.uint8) * 255
cv2.addWeighted(bg, opacity, img, 1 - opacity, 0, img)
cv2.imshow('Hostage', img)
cv2.waitKey(rate)
Example #27
| Source File: waterworld.py From MADRL with MIT License | 4 votes |
|
def render(self, screen_size=800, rate=10, mode='human'):
import cv2
img = np.empty((screen_size, screen_size, 3), dtype=np.uint8)
img[...] = 255
# Obstacles
for iobs, obstaclex_2 in enumerate(self.obstaclesx_No_2):
assert obstaclex_2.shape == (2,)
color = (128, 128, 0)
cv2.circle(img,
tuple((obstaclex_2 * screen_size).astype(int)),
int(self.obstacle_radius * screen_size), color, -1, lineType=cv2.CV_AA)
# Pursuers
for pursuer in self._pursuers:
for k in range(pursuer._n_sensors):
color = (0, 0, 0)
cv2.line(img,
tuple((pursuer.position * screen_size).astype(int)),
tuple(((pursuer.position + pursuer._sensor_range * pursuer.sensors[k]) *
screen_size).astype(int)), color, 1, lineType=cv2.CV_AA)
cv2.circle(img,
tuple((pursuer.position * screen_size).astype(int)),
int(pursuer._radius * screen_size), (255, 0, 0), -1, lineType=cv2.CV_AA)
# Evaders
for evader in self._evaders:
color = (0, 255, 0)
cv2.circle(img,
tuple((evader.position * screen_size).astype(int)),
int(evader._radius * screen_size), color, -1, lineType=cv2.CV_AA)
# Poison
for poison in self._poisons:
color = (0, 0, 255)
cv2.circle(img,
tuple((poison.position * screen_size).astype(int)),
int(poison._radius * screen_size), color, -1, lineType=cv2.CV_AA)
opacity = 0.4
bg = np.ones((screen_size, screen_size, 3), dtype=np.uint8) * 255
cv2.addWeighted(bg, opacity, img, 1 - opacity, 0, img)
cv2.imshow('Waterworld', img)
cv2.waitKey(rate)
return np.asarray(img)[..., ::-1]
Example #28
| Source File: object-tracking.py From rpi-opencv with GNU General Public License v3.0 | 4 votes |
|
def run_main():
cap = cv2.VideoCapture('crash-480.mp4')
#cap.set(3,320)
#cap.set(4,240)
# Read the first frame of the video
ret, frame = cap.read()
# Set the ROI (Region of Interest). Actually, this is a
# rectangle of the building that we're tracking
c,r,w,h = 427,240,50,50
track_window = (c,r,w,h)
# Create mask and normalized histogram
roi = frame[r:r+h, c:c+w]
hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((0., 30.,32.)), np.array((180.,255.,255.)))
roi_hist = cv2.calcHist([hsv_roi], [0], mask, [180], [0, 180])
cv2.normalize(roi_hist, roi_hist, 0, 255, cv2.NORM_MINMAX)
term_crit = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 80, 1)
while True:
t = cv2.getTickCount()
ret, frame = cap.read()
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
dst = cv2.calcBackProject([hsv], [0], roi_hist, [0,180], 1)
ret, track_window = cv2.meanShift(dst, track_window, term_crit)
x,y,w,h = track_window
cv2.rectangle(frame, (x,y), (x+w,y+h), 255, 2)
cv2.putText(frame, 'Tracked', (x-25,y-10), cv2.FONT_HERSHEY_SIMPLEX,
.5, (255,255,255), 1, cv2.CV_AA)
t = cv2.getTickCount() - t
print "detection time = %gms" % (t/(cv2.getTickFrequency()*1000.))
cv2.imshow('Tracking', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
Example #29
| Source File: handpose_evaluation.py From deep-prior-pp with GNU General Public License v3.0 | 4 votes |
|
def plotJoints(self, ax, joint, color='nice', jcolor=None, annoscale=1):
"""
Plot connected joints
:param ax: axis to plot on
:param joint: joints to connect
:param color: line color
"""
if joint.shape[0] >= numpy.max(self.jointConnections):
for i in range(len(self.jointConnections)):
if isinstance(ax, numpy.ndarray):
if color == 'nice':
lc = tuple((self.jointConnectionColors[i]*255.).astype(int))
elif color == 'gray':
lc = tuple((rgb_to_gray(self.jointConnectionColors[i])*255.).astype(int))
else:
lc = color
cv2.line(ax, (int(numpy.rint(joint[self.jointConnections[i][0], 0])),
int(numpy.rint(joint[self.jointConnections[i][0], 1]))),
(int(numpy.rint(joint[self.jointConnections[i][1], 0])),
int(numpy.rint(joint[self.jointConnections[i][1], 1]))),
lc, thickness=3*annoscale, lineType=cv2.CV_AA)
else:
if color == 'nice':
lc = self.jointConnectionColors[i]
elif color == 'gray':
lc = rgb_to_gray(self.jointConnectionColors[i])
else:
lc = color
ax.plot(numpy.hstack((joint[self.jointConnections[i][0], 0], joint[self.jointConnections[i][1], 0])),
numpy.hstack((joint[self.jointConnections[i][0], 1], joint[self.jointConnections[i][1], 1])),
c=lc, linewidth=3.0*annoscale)
for i in range(joint.shape[0]):
if isinstance(ax, numpy.ndarray):
if jcolor == 'nice':
jc = tuple((self.jointColors[i]*255.).astype(int))
elif jcolor == 'gray':
jc = tuple((rgb_to_gray(self.jointColors[i])*255.).astype(int))
else:
jc = jcolor
cv2.circle(ax, (int(numpy.rint(joint[i, 0])), int(numpy.rint(joint[i, 1]))), 6*annoscale,
jc, thickness=-1, lineType=cv2.CV_AA)
else:
if jcolor == 'nice':
jc = self.jointColors[i]
elif jcolor == 'gray':
jc = rgb_to_gray(self.jointColors[i])
else:
jc = jcolor
ax.scatter(joint[i, 0], joint[i, 1], marker='o', s=100,
c=jc)
Example #30
| Source File: viz.py From Object_Detection_Tracking with Apache License 2.0 | 4 votes |
|
def vis_keypoints(img, kps, kp_thresh=2, alpha=0.7):
"""Visualizes keypoints (adapted from vis_one_image).
kps has shape (4, #keypoints) where 4 rows are (x, y, logit, prob).
"""
dataset_keypoints, _ = get_keypoints()
kp_lines = kp_connections(dataset_keypoints)
# Convert from plt 0-1 RGBA colors to 0-255 BGR colors for opencv.
cmap = plt.get_cmap('rainbow')
colors = [cmap(i) for i in np.linspace(0, 1, len(kp_lines) + 2)]
colors = [(c[2] * 255, c[1] * 255, c[0] * 255) for c in colors]
# Perform the drawing on a copy of the image, to allow for blending.
kp_mask = np.copy(img)
# Draw mid shoulder / mid hip first for better visualization.
mid_shoulder = (
kps[:2, dataset_keypoints.index('right_shoulder')] +
kps[:2, dataset_keypoints.index('left_shoulder')]) / 2.0
sc_mid_shoulder = np.minimum(
kps[2, dataset_keypoints.index('right_shoulder')],
kps[2, dataset_keypoints.index('left_shoulder')])
mid_hip = (
kps[:2, dataset_keypoints.index('right_hip')] +
kps[:2, dataset_keypoints.index('left_hip')]) / 2.0
sc_mid_hip = np.minimum(
kps[2, dataset_keypoints.index('right_hip')],
kps[2, dataset_keypoints.index('left_hip')])
nose_idx = dataset_keypoints.index('nose')
if sc_mid_shoulder > kp_thresh and kps[2, nose_idx] > kp_thresh:
cv2.line(
kp_mask, int_it(tuple(mid_shoulder)), int_it(tuple(kps[:2, nose_idx])),
color=colors[len(kp_lines)], thickness=2, lineType=cv2.CV_AA)
if sc_mid_shoulder > kp_thresh and sc_mid_hip > kp_thresh:
cv2.line(
kp_mask, int_it(tuple(mid_shoulder)), int_it(tuple(mid_hip)),
color=colors[len(kp_lines) + 1], thickness=2, lineType=cv2.CV_AA)
# Draw the keypoints.
for l in range(len(kp_lines)):
i1 = kp_lines[l][0]
i2 = kp_lines[l][1]
p1 = int(kps[0, i1]), int(kps[1, i1])
p2 = int(kps[0, i2]), int(kps[1, i2])
if kps[2, i1] > kp_thresh and kps[2, i2] > kp_thresh:
cv2.line(
kp_mask, p1, p2,
color=colors[l], thickness=2, lineType=cv2.CV_AA)
if kps[2, i1] > kp_thresh:
cv2.circle(
kp_mask, p1,
radius=3, color=colors[l], thickness=-1, lineType=cv2.CV_AA)
if kps[2, i2] > kp_thresh:
cv2.circle(
kp_mask, p2,
radius=3, color=colors[l], thickness=-1, lineType=cv2.CV_AA)
# Blend the keypoints.
return cv2.addWeighted(img, 1.0 - alpha, kp_mask, alpha, 0)
