我们从Python开源项目中，提取了以下50个代码示例，用于说明如何使用cv2.circle()。
def image_callback(self, msg): image = self.bridge.imgmsg_to_cv2(msg,desired_encoding='bgr8') hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) lower_yellow = numpy.array([18, 120, 200]) upper_yellow = numpy.array([28, 255, 255]) mask = cv2.inRange(hsv, lower_yellow, upper_yellow) h, w, d = image.shape search_top = 3*h/4 search_bot = 3*h/4 + 20 mask[0:search_top, 0:w] = 0 mask[search_bot:h, 0:w] = 0 M = cv2.moments(mask) if M['m00'] > 0: cx = int(M['m10']/M['m00']) cy = int(M['m01']/M['m00']) cv2.circle(image, (cx, cy), 20, (0,0,255), -1) # BEGIN CONTROL err = cx - w/2 self.twist.linear.x = 0.2 self.twist.angular.z = -float(err) / 100 self.cmd_vel_pub.publish(self.twist) # END CONTROL cv2.imshow("window", image) cv2.waitKey(3)
def draw_termites(self): """Draw termites on simulation. Args: None. Returns: None. """ for termite in self.termites: cv2.circle(self.background, termite.trail[self.current_step], self.params['termite_radius'], termite.color, 2) cv2.circle(self.background, termite.trail[self.current_step], 2, termite.color, -1) cv2.putText(self.background, termite.number, (termite.trail[self.current_step][0] - 4, termite.trail[self.current_step][1] - self.params['termite_radius'] - 5), 2, color=termite.color, fontScale=0.4) cv2.circle(self.video_source.current_frame, termite.trail[self.current_step], self.params['termite_radius'], termite.color, 2) cv2.circle(self.video_source.current_frame, termite.trail[self.current_step], 2, termite.color, -1) cv2.putText(self.video_source.current_frame, termite.number, (termite.trail[self.current_step][0] - 4, termite.trail[self.current_step][1] - self.params['termite_radius'] - 5), 2, color=termite.color, fontScale=0.4)
def draw_joints_15(test_image, joints, save_image): image = cv2.imread(test_image) # bounding box bbox = [min(joints[:, 0]), min(joints[:, 1]), max(joints[:, 0]), max(joints[:, 1])] # draw bounding box in red rectangle cv2.rectangle(image, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (0, 0, 255), 2) # draw joints in green spots for j in xrange(len(joints)): cv2.circle(image, (joints[j, 0], joints[j, 1]), 5, (0, 255, 0), 1) # draw torso in yellow lines torso = [[0, 1], [0, 14], [5, 10]] for item in torso: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (0, 255, 255), 1) # draw left part in pink lines lpart = [[14, 13], [13, 12], [12, 11], [13, 10], [10, 9], [9, 8]] for item in lpart: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (255, 0, 255), 1) # draw right part in blue lines rpart = [[1, 2], [2, 3], [3, 4], [2, 5], [5, 6], [6, 7]] for item in rpart: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (255, 0, 0), 1) cv2.imwrite(save_image, image)
def draw_circle(img, radius, x, y): """ Render circle :param img : Canvas :param radius : Radius of the circle :param x : (x, y) is the center of the circle graph on the canvas :param y : (x, y) is the center of the circle graph on the canvas """ ############################################################ # Write your code here! # ############################################################ cv2.circle(img, (x, y), radius, (20, 215, 20), radius) ############################################################ # End # ############################################################
def transparent_circle(img,center,radius,color,thickness): center = tuple(map(int,center)) rgb = [255*c for c in color[:3]] # convert to 0-255 scale for OpenCV alpha = color[-1] radius = int(radius) if thickness > 0: pad = radius + 2 + thickness else: pad = radius + 3 roi = slice(center[1]-pad,center[1]+pad),slice(center[0]-pad,center[0]+pad) try: overlay = img[roi].copy() cv2.circle(img,center,radius,rgb, thickness=thickness, lineType=cv2.LINE_AA) opacity = alpha cv2.addWeighted(src1=img[roi], alpha=opacity, src2=overlay, beta=1. - opacity, gamma=0, dst=img[roi]) except: logger.debug("transparent_circle would have been partially outside of img. Did not draw it.")
def brush_circle(event, x, y, flags, param): global ix, iy, drawing, mode, r,g,b,radius if event == cv2.EVENT_LBUTTONDOWN: drawing = True # start to draw when L button down ix, iy = x, y elif event == cv2.EVENT_MOUSEMOVE: if drawing == True and mode == True: cv2.circle(img, (x,y), radius, (b, g, r), -1) elif event == cv2.EVENT_LBUTTONUP: drawing = False # end drawing when L button up if mode == True: cv2.circle(img, (x,y), radius, (b, g, r), -1) # Create a black image, a window
def draw_flow(img, flow, step=8): h, w = img.shape[:2] y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1).astype(int) fx, fy = flow[y,x].T lines = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2) lines = np.int32(lines + 0.5) vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) cv2.polylines(vis, lines, 0, (0, 255, 0)) for (x1, y1), (x2, y2) in lines: cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1) return vis ##################################################################### # define video capture object
def draw_circle(event,x,y,flags,param): global ix,iy,drawing,mode if event == cv2.EVENT_LBUTTONDOWN: drawing = True ix,iy = x,y elif event == cv2.EVENT_MOUSEMOVE: if drawing == True: if mode == True: cv2.rectangle(img,(ix,iy),(x,y),(0,255,0),-1) else: cv2.circle(img,(x,y),5,(0,0,255),-1) elif event == cv2.EVENT_LBUTTONUP: drawing = False if mode == True: cv2.rectangle(img,(ix,iy),(x,y),(0,255,0),-1) else: cv2.circle(img,(x,y),5,(0,0,255),-1)
def draw_circle(event,x,y,flags,param): global drawing,drawing1 if event == cv2.EVENT_LBUTTONDOWN: drawing = True if event == cv2.EVENT_RBUTTONDOWN: drawing1 = True if event == cv2.EVENT_MOUSEMOVE: if drawing == True: cv2.circle(img,(x,y),5,(0,0,255),-1) if drawing1 == True: cv2.circle(img,(x,y),5,(0,255,0),-1) if event == cv2.EVENT_LBUTTONUP: drawing = False if event == cv2.EVENT_RBUTTONUP: drawing1 = False #print (drawing)
def find_center(self, name, frame, mask, min_radius): if name not in self.pts: self.pts[name] = deque(maxlen=self.params['tracking']['buffer_size']) # find contours in the mask and initialize the current (x, y) center of the ball cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2] # only proceed if at least one contour was found if len(cnts) > 0: # find the largest contour in the mask, then use it to compute the minimum enclosing circle and centroid c = max(cnts, key=cv2.contourArea) ((x, y), radius) = cv2.minEnclosingCircle(c) center = (int(x), int(y)) # only proceed if the radius meets a minimum size if radius > min_radius: # draw the circle and centroid on the frame, then update the list of tracked points cv2.circle(frame, center, int(radius), (0, 255, 255), 2) cv2.circle(frame, center, 5, (0, 0, 255), -1) self.pts[name].appendleft(center) smooth_points = 8 return (int(np.mean([self.pts[name][i][0] for i in range(min(smooth_points, len(self.pts[name])))])), int(np.mean([self.pts[name][i][1] for i in range(min(smooth_points, len(self.pts[name])))]))), radius return None, None
def mark_hand_center(frame_in,cont): max_d=0 pt=(0,0) x,y,w,h = cv2.boundingRect(cont) for ind_y in xrange(int(y+0.3*h),int(y+0.8*h)): #around 0.25 to 0.6 region of height (Faster calculation with ok results) for ind_x in xrange(int(x+0.3*w),int(x+0.6*w)): #around 0.3 to 0.6 region of width (Faster calculation with ok results) dist= cv2.pointPolygonTest(cont,(ind_x,ind_y),True) if(dist>max_d): max_d=dist pt=(ind_x,ind_y) if(max_d>radius_thresh*frame_in.shape[1]): thresh_score=True cv2.circle(frame_in,pt,int(max_d),(255,0,0),2) else: thresh_score=False return frame_in,pt,max_d,thresh_score # 6. Find and display gesture
def draw_joints(test_image, joints, save_image): image = cv2.imread(test_image) joints = np.vstack((joints, (joints[8, :] + joints[11, :])/2)) # bounding box bbox = [min(joints[:, 0]), min(joints[:, 1]), max(joints[:, 0]), max(joints[:, 1])] # draw bounding box in red rectangle cv2.rectangle(image, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (0, 0, 255), 2) # draw joints in green spots for j in xrange(len(joints)): cv2.circle(image, (joints[j, 0], joints[j, 1]), 5, (0, 255, 0), 2) # draw torso in yellow lines torso = [[0, 1], [1, 14], [2, 14], [5, 14]] for item in torso: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (0, 255, 255), 2) # draw left part in pink lines lpart = [[1, 5], [5, 6], [6, 7], [5, 14], [14, 11], [11, 12], [12, 13]] for item in lpart: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (255, 0, 255), 2) # draw right part in blue lines rpart = [[1, 2], [2, 3], [3, 4], [2, 14], [14, 8], [8, 9], [9, 10]] for item in rpart: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (255, 0, 0), 2) cv2.imwrite(save_image, image)
def draw_flow(img, flow, step=16): h, w = img.shape[:2] y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1) fx, fy = flow[y,x].T m = np.bitwise_and(np.isfinite(fx), np.isfinite(fy)) lines = np.vstack([x[m], y[m], x[m]+fx[m], y[m]+fy[m]]).T.reshape(-1, 2, 2) lines = np.int32(lines + 0.5) vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) cv2.polylines(vis, lines, 0, (0, 255, 0)) for (x1, y1), (x2, y2) in lines: cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1) return vis
def plot_points(image, points, color=(0, 0, 255)): """Draw circles at given locations on image. Arguments: image -- Image to draw on. points -- x,y pairs of points to plot. """ # find best radius for image image_width = image.shape[1] radius = int(image_width / 400) # draw for point in points: point = tuple(map(int, point)) cv2.circle(image, point, color=color, radius=radius, thickness=radius/2)
def _get_mask(self, scan, slide, series): img, s, o, origShape = scan mask = np.zeros((origShape[1], origShape[2])) nodules = self._nodule_info[series] for nodule in nodules: iid, z, edges = nodule z = int((z - o[2])/s[2]) if z == slide: if edges.shape[0] > 1: cv.fillPoly(mask, [edges], 255) else: #It's a small nodule. Make a circle of radius 3mm edges = np.squeeze(edges) center = tuple(edges) radius = max(3.0/s[0], 3.0/s[1]) cv.circle(mask, center, int(radius+1), 255, -1) if img.shape[1] != origShape[1] or img.shape[2] != origShape[2]: mask = imu.resize_2d(mask, (img.shape[1], img.shape[2])) return mask
def draw_circle( event, x,y,flags, param): global ix, iy, drawing, mode if event == cv2.EVENT_LBUTTONDOWN: drawing = True ix, iy = x, y elif event == cv2.EVENT_MOUSEMOVE: if drawing == True: if mode == True: cv2.rectangle( img, (ix, iy), (x,y),(0,255,0), 1) # -1 for last argument like CV_FILLED else: cv2.circle( img, (x,y), 5, (0,0,255), -1) elif event == cv2.EVENT_LBUTTONUP: drawing = False if mode == True: cv2.rectangle( img, (ix, iy), (x,y), (0,255,0), 1) else: cv2.circle(img, (x,y), 5, (0,0,255),-1)
def execute_BlobDetector(proxy,obj): try: img=obj.sourceObject.Proxy.img.copy() except: img=cv2.imread(__dir__+'/icons/freek.png') im = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) im=255-im im2 = img params = cv2.SimpleBlobDetector_Params() params.filterByArea = True params.minArea = obj.Area params.filterByConvexity = True params.minConvexity = obj.Convexity/200 # Set up the detector with default parameters. detector = cv2.SimpleBlobDetector_create(params) # Detect blobs. keypoints = detector.detect(im) # Draw detected blobs as red circles. # cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS ensures the size of the circle corresponds to the size of blob if not obj.showBlobs: im_with_keypoints = cv2.drawKeypoints(im, keypoints, np.array([]), (0,0,255), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS) obj.Proxy.img = im_with_keypoints for k in keypoints: (x,y)=k.pt x=int(round(x)) y=int(round(y)) # cv2.circle(im,(x,y),4,0,5) cv2.circle(im,(x,y),4,255,5) cv2.circle(im,(x,y),4,0,5) im[y,x]=255 im[y,x]=0 obj.Proxy.img = cv2.cvtColor(im, cv2.COLOR_GRAY2BGR) else: for k in keypoints: (x,y)=k.pt x=int(round(x)) y=int(round(y)) cv2.circle(im2,(x,y),4,(255,0,0),5) cv2.circle(im2,(x,y),4,(0,0,0),5) im2[y,x]=(255,0,0) im2[y,x]=(0,0,0) obj.Proxy.img = im2
def execute_GoodFeaturesToTrack(proxy,obj): ''' https://opencv-python-tutroals.readthedocs.org/en/latest/py_tutorials/py_feature2d/py_shi_tomasi/py_shi_tomasi.html ''' try: img=obj.sourceObject.Proxy.img.copy() except: img=cv2.imread(__dir__+'/icons/freek.png') gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) corners = cv2.goodFeaturesToTrack(gray,obj.maxCorners,obj.qualityLevel,obj.minDistance) corners = np.int0(corners) for i in corners: x,y = i.ravel() cv2.circle(img,(x,y),3,255,-1) obj.Proxy.img = img
def detectmarker(image): grayscale = getgrayimage(image) mkradius = getapproxmarkerradius(grayscale) # approximate marker radius marker = cv2.resize(MARKER, (mkradius*2, mkradius*2)) # resize the marker #template matching matched = cv2.matchTemplate(grayscale, marker, cv2.TM_CCORR_NORMED) #returns float32 #detect 4 greatest values markerposarray = [] for i in range(4): (minval, maxval, minloc, maxloc) = cv2.minMaxLoc(matched) markerposarray.append(tuple(map(lambda x: x+mkradius, maxloc))) cv2.circle(matched, maxloc, mkradius, (0.0), -1) #ignore near the current minloc return markerposarray
def init_mask(self, event, x, y, flags, param): self._thickness = 3 # The thickness in drawing; self._WHITE = [255, 255, 255] # Pure white; # Draw a point on the image; if event == cv2.EVENT_RBUTTONDOWN: if self._drawing == True: cv2.circle(self.img, (x, y), self._thickness, self._WHITE, -1) self.mask[y-self._thickness:y+self._thickness, x-self._thickness:x+self._thickness] = self._SHADOW self._shadow_seed = self.img[y-self._thickness:y+self._thickness, x-self._thickness:x+self._thickness].copy() elif event == cv2.EVENT_RBUTTONUP: if self._drawing == True: self._drawing = False self._drawn = True cv2.circle(self.img, (x, y), self._thickness, self._WHITE, -1)
def mark_point(img, x, y): """ Mark a point Args: - img(numpy): the source image - x, y(int): position """ overlay = img.copy() output = img.copy() alpha = 0.5 radius = max(5, min(img.shape[:2])//15) center = int(x), int(y) color = (0, 0, 255) cv2.circle(overlay, center, radius, color, -1) cv2.addWeighted(overlay, alpha, output, 1-alpha, 0, output) return output
def do_draw(self, event, x, y, flags, param): draw_vals = {1: 100, 2: 0} if event == cv2.EVENT_LBUTTONUP or event == cv2.EVENT_RBUTTONUP: self.drawing = 0 elif event == cv2.EVENT_LBUTTONDOWN: self.drawing = 1 elif event == cv2.EVENT_RBUTTONDOWN: self.drawing = 2 elif self.drawing != 0: cv2.circle(self.img, (x, y), 5, draw_vals[self.drawing], -1)
def facial_landmark_detection(image, detector, predictor, file): gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) img_size = gray.shape landmark_faces = detector(gray, 1) faces = list() area = 0 face_idx = 0 bItr = False for (idx, landmark_faces) in enumerate(landmark_faces): shape = predictor(gray, landmark_faces) shape = shape_to_np(shape) (x, y, w, h) = rect_to_bb(landmark_faces, img_size, file) if (w * h) > area: area = w * h faces = [x, y, w, h] bItr = True #cv2.rectangle(image, (x, y), (x + w, y + h), (0, 0, 255), 2) #cv2.putText(image, "Face #{}".format(idx + 1), (x - 10, y - 10), \ # cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2) #for (x, y) in shape: # cv2.circle(image, (x, y), 1, (0, 0, 255), -1) return bItr, faces
def side_intersect(self, image, contours, row, markup=True): """ Find intersections to both sides along a row """ if markup: cv2.line(image, (0, row), (image.shape[1], row), (0, 0, 255), 1) cnt_l, col_l = self.find_intersect(image, contours, row, -1) if markup and cnt_l is not None: cv2.drawContours(image, [contours[cnt_l]], -1, (0, 255, 255), -1) cv2.circle(image, (col_l, row), 4, (0, 255, 0), 2) cnt_r, col_r = self.find_intersect(image, contours, row, 1) if markup and cnt_r is not None: cv2.drawContours(image, [contours[cnt_r]], -1, (255, 255, 0), -1) cv2.circle(image, (col_r, row), 4, (0, 255, 0), 2) return (cnt_l, col_l), (cnt_r, col_r)
def draw_humans(img, human_list): img_copied = np.copy(img) image_h, image_w = img_copied.shape[:2] centers = {} for human in human_list: part_idxs = human.keys() # draw point for i in range(CocoPart.Background.value): if i not in part_idxs: continue part_coord = human[i][1] center = (int(part_coord[0] * image_w + 0.5), int(part_coord[1] * image_h + 0.5)) centers[i] = center cv2.circle(img_copied, center, 3, CocoColors[i], thickness=3, lineType=8, shift=0) # draw line for pair_order, pair in enumerate(CocoPairsRender): if pair[0] not in part_idxs or pair[1] not in part_idxs: continue img_copied = cv2.line(img_copied, centers[pair[0]], centers[pair[1]], CocoColors[pair_order], 3) return img_copied
def _show(self, path, inpmat, heatmat, pafmat, humans): image = cv2.imread(path) # CocoPoseLMDB.display_image(inpmat, heatmat, pafmat) image_h, image_w = image.shape[:2] heat_h, heat_w = heatmat.shape[:2] for _, human in humans.items(): for part in human: if part['partIdx'] not in common.CocoPairsRender: continue center1 = (int((part['c1'][0] + 0.5) * image_w / heat_w), int((part['c1'][1] + 0.5) * image_h / heat_h)) center2 = (int((part['c2'][0] + 0.5) * image_w / heat_w), int((part['c2'][1] + 0.5) * image_h / heat_h)) cv2.circle(image, center1, 2, (255, 0, 0), thickness=3, lineType=8, shift=0) cv2.circle(image, center2, 2, (255, 0, 0), thickness=3, lineType=8, shift=0) cv2.putText(image, str(part['partIdx'][1]), center2, cv2.FONT_HERSHEY_DUPLEX, 0.5, (255, 0, 0), 1) image = cv2.line(image, center1, center2, (255, 0, 0), 1) cv2.imshow('result', image) cv2.waitKey(0)
def draw(event, x, y, flags, param): global drawing, ix, iy, shape, canvas, brush if event == cv2.EVENT_LBUTTONDOWN: drawing = True ix, iy = x, y elif event == cv2.EVENT_MOUSEMOVE: if drawing == True: if shape == 1: cv2.circle(canvas, (x, y), pencil, color, -1) elif shape == 2: cv2.circle(canvas, (x, y), brush, color, -1) elif shape == 3: cv2.circle(canvas, (x, y), eraser, (255, 255, 255), -1) elif shape == 5: cv2.rectangle(canvas, (ix, iy), (x, y), color, -1) elif shape == 6: cv2.circle(canvas, (x, y), calc_radius(x, y), color, -1) elif event == cv2.EVENT_LBUTTONUP: drawing = False if shape == 1: cv2.circle(canvas, (x, y), pencil, color, -1) elif shape == 2: cv2.circle(canvas, (x, y), brush, color, -1) elif shape == 3: cv2.circle(canvas, (x, y), eraser, (255, 255, 255), -1) elif shape == 4: cv2.line(canvas, (ix, iy), (x, y), color, pencil) elif shape == 5: cv2.rectangle(canvas, (ix, iy), (x, y), color, -1) elif shape == 6: cv2.circle(canvas, (x, y), calc_radius(x, y), color, -1)
def saveAnnotatedSample(self, path): skel2 = self.crop2D() skel2 = skel2.reshape(-1, 3) for i, pt in enumerate(skel2): skel2[i] = Camera.to2D(pt) print 'current camera option={}'.format(Camera.focal_x) skel = self.skel skel.shape = (-1,3) dm = self.norm_dm.copy() dm[dm == Camera.far_point] = 0 ax = fig.add_subplot(121) img = dm.copy() img = img - img.min() img *= 255/img.max() for pt in skel2: cv2.circle(img, (pt[0], pt[1]), 2, (255,0,0), -1) cv2.imwrite(path, img)
def vis_pose(normed_vec): import depth origin_pt = np.array([0,0,depth.DepthMap.invariant_depth]) vec = normed_vec.copy()*50.0 vec.shape = (-1,3) offset_x = Camera.center_x - depth.DepthMap.size2[0]/2 offset_y = Camera.center_y - depth.DepthMap.size2[1]/2 img = np.ones((depth.DepthMap.size2[0], depth.DepthMap.size2[1]))*255 img = cv2.cvtColor(img.astype('uint8'), cv2.COLOR_GRAY2BGR) for idx, pt3 in enumerate(vec): pt = Camera.to2D(pt3+origin_pt) pt = (pt[0]-offset_x, pt[1]-offset_y) cv2.circle(img, (int(pt[0]), int(pt[1])),2, (255,0,0), -1) return img
def draw_images(self, frame, hsv, mask_ball, mask_arena, arena_center, arena_ring_radius=None): self.draw_history(frame, 'ball') self.draw_history(frame, 'arena') if arena_ring_radius is not None: cv2.circle(frame, arena_center, arena_ring_radius, (0, 128, 255), 2) return frame #rgbs = cv2.split(frame) #hsvs = cv2.split(hsv) #cv2.imshow("Hue", hsvs[0]) #cv2.imshow("Mask ball", mask_ball) #cv2.imshow("Mask arena", mask_arena) #cv2.imshow("Frame", frame) #cv2.waitKey(1) #cv2.imshow("Red", rgbs[0]) #cv2.imshow("Green", rgbs[1]) #cv2.imshow("Blue", rgbs[2]) #cv2.imshow("Saturation", hsvs[1]) #cv2.imshow("Value", hsvs[2]) #cv2.waitKey(1)
def update(dummy=None): if seed_pt is None: cv2.imshow('floodfill', img) return flooded = img.copy() mask[:] = 0 lo = cv2.getTrackbarPos('lo', 'floodfill') hi = cv2.getTrackbarPos('hi', 'floodfill') flags = connectivity if fixed_range: flags |= cv2.FLOODFILL_FIXED_RANGE cv2.floodFill(flooded, mask, seed_pt, (255, 255, 255), (lo,)*3, (hi,)*3, flags) cv2.circle(flooded, seed_pt, 2, (0, 0, 255), -1) cv2.imshow('floodfill', flooded)
def draw_flow(img, flow, step=16): h, w = img.shape[:2] y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2, -1).astype(int) # ????????????????????????16?reshape?2??array fx, fy = flow[y, x].T # ??????????????? lines = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2) # ????????????2*2??? lines = np.int32(lines + 0.5) # ???????????? vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) cv2.polylines(vis, lines, 0, (0, 255, 0)) # ??????????????? for (x1, y1), (x2, y2) in lines: cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1) # ??????????????????? return vis
def draw_circles(self): """ Draw a circle for each contour in self.candidates """ # Just false positives if len(self.candidates) < 4: return for con in self.candidates: if con.width: cv2.circle(self.image, (con.cX, con.cY), int(con.width/2), (255, 255, 255), 2)
def draw_correspondences(img, dstpoints, projpts): display = img.copy() dstpoints = norm2pix(img.shape, dstpoints, True) projpts = norm2pix(img.shape, projpts, True) for pts, color in [(projpts, (255, 0, 0)), (dstpoints, (0, 0, 255))]: for point in pts: cv2.circle(display, fltp(point), 3, color, -1, cv2.LINE_AA) for point_a, point_b in zip(projpts, dstpoints): cv2.line(display, fltp(point_a), fltp(point_b), (255, 255, 255), 1, cv2.LINE_AA) return display
def visualize_contours(name, small, cinfo_list): regions = np.zeros_like(small) for j, cinfo in enumerate(cinfo_list): cv2.drawContours(regions, [cinfo.contour], 0, CCOLORS[j % len(CCOLORS)], -1) mask = (regions.max(axis=2) != 0) display = small.copy() display[mask] = (display[mask]/2) + (regions[mask]/2) for j, cinfo in enumerate(cinfo_list): color = CCOLORS[j % len(CCOLORS)] color = tuple([c/4 for c in color]) cv2.circle(display, fltp(cinfo.center), 3, (255, 255, 255), 1, cv2.LINE_AA) cv2.line(display, fltp(cinfo.point0), fltp(cinfo.point1), (255, 255, 255), 1, cv2.LINE_AA) debug_show(name, 1, 'contours', display)
def visualize_span_points(name, small, span_points, corners): display = small.copy() for i, points in enumerate(span_points): points = norm2pix(small.shape, points, False) mean, small_evec = cv2.PCACompute(points.reshape((-1, 2)), None, maxComponents=1) dps = np.dot(points.reshape((-1, 2)), small_evec.reshape((2, 1))) dpm = np.dot(mean.flatten(), small_evec.flatten()) point0 = mean + small_evec * (dps.min()-dpm) point1 = mean + small_evec * (dps.max()-dpm) for point in points: cv2.circle(display, fltp(point), 3, CCOLORS[i % len(CCOLORS)], -1, cv2.LINE_AA) cv2.line(display, fltp(point0), fltp(point1), (255, 255, 255), 1, cv2.LINE_AA) cv2.polylines(display, [norm2pix(small.shape, corners, True)], True, (255, 255, 255)) debug_show(name, 3, 'span points', display)
def draw_joints_13(test_image, joints, save_image): image = cv2.imread(test_image) # bounding box bbox = [min(joints[:, 0]), min(joints[:, 1]), max(joints[:, 0]), max(joints[:, 1])] # draw bounding box in red rectangle cv2.rectangle(image, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (0, 0, 255), 2) # draw joints in green spots for j in xrange(len(joints)): cv2.circle(image, (joints[j, 0], joints[j, 1]), 5, (0, 255, 0), 2) # draw torso in yellow lines torso = [[0, 1], [1, 8]] for item in torso: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (0, 255, 255), 2) # draw left part in pink lines lpart = [[1, 3], [3, 5], [5, 7], [3, 8], [8, 10], [10, 12]] for item in lpart: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (255, 0, 255), 2) # draw right part in blue lines rpart = [[1, 2], [2, 4], [4, 6], [2, 8], [8, 9], [9, 11]] for item in rpart: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (255, 0, 0), 2) cv2.imwrite(save_image, image)
def draw_joints_17(test_image, joints, save_image): image = cv2.imread(test_image) # bounding box bbox = [min(joints[:, 0]), min(joints[:, 1]), max(joints[:, 0]), max(joints[:, 1])] # draw bounding box in red rectangle cv2.rectangle(image, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (0, 0, 255), 2) # draw joints in green spots for j in xrange(len(joints)): cv2.circle(image, (joints[j, 0], joints[j, 1]), 5, (0, 255, 0), 2) # draw head in yellow lines head = [[0, 1], [0, 2], [1, 3], [2, 4], [3, 5], [4, 6]] for item in head: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (0, 255, 255), 2) # draw upper part in pink lines upart = [[5, 6], [5, 7], [6, 8], [7, 9], [8, 10], [5, 11], [6, 12], [11, 12]] for item in upart: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (255, 0, 255), 2) # draw lower part in blue lines lpart = [[11, 13], [12, 14], [13, 15], [14, 16]] for item in lpart: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (255, 0, 0), 2) cv2.imwrite(save_image, image)
def draw_gt_market(test_image, joints, save_image): image = cv2.imread(test_image) # draw joints in green spots for j in xrange(len(joints) / 2): cv2.circle(image, (joints[j * 2], joints[j * 2 + 1]), 2, (0, 255, 0), 1) # draw torso in yellow lines p1 = [0, 0, 5] p2 = [1, 14, 10] for j in xrange(len(p1)): cv2.line(image, (joints[p1[j] * 2], joints[p1[j] * 2 + 1]), (joints[p2[j] * 2], joints[p2[j] * 2 + 1]), (0, 255, 255), 1) # draw left part in pink lines p1 = [14, 13, 12, 13, 10, 9] p2 = [13, 12, 11, 10, 9, 8] for j in xrange(len(p1)): cv2.line(image, (joints[p1[j] * 2], joints[p1[j] * 2 + 1]), (joints[p2[j] * 2], joints[p2[j] * 2 + 1]), (255, 0, 255), 1) # draw right part in blue lines p1 = [1, 2, 3, 2, 5, 6] p2 = [2, 3, 4, 5, 6, 7] for j in xrange(len(p1)): cv2.line(image, (joints[p1[j] * 2], joints[p1[j] * 2 + 1]), (joints[p2[j] * 2], joints[p2[j] * 2 + 1]), (255, 0, 0), 1) cv2.imwrite(save_image, image)
def draw_joints_16(test_image, joints, save_image): image = cv2.imread(test_image) # bounding box bbox = [min(joints[:, 0]), min(joints[:, 1]), max(joints[:, 0]), max(joints[:, 1])] # draw bounding box in red rectangle cv2.rectangle(image, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (0, 0, 255), 2) # draw joints in green spots for j in xrange(len(joints)): cv2.circle(image, (joints[j, 0], joints[j, 1]), 5, (0, 255, 0), 2) # draw torso in yellow lines torso = [[9, 8], [8, 7], [7, 6]] for item in torso: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (0, 255, 255), 2) # draw left part in pink lines lpart = [[8, 13], [13, 14], [14, 15], [13, 6], [6, 3], [3, 4], [4, 5]] for item in lpart: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (255, 0, 255), 2) # draw right part in blue lines rpart = [[8, 12], [12, 11], [11, 10], [12, 6], [6, 2], [2, 1], [1, 0]] for item in rpart: cv2.line(image, (joints[item[0], 0], joints[item[0], 1]), (joints[item[1], 0], joints[item[1], 1]), (255, 0, 0), 2) cv2.imwrite(save_image, image)
