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.putText()。
def draw_rects(img, rects): """ ????????????? :param img: :param rects: :return: """ for x, y, w, h in rects: cv2.rectangle(img, (x, y), (x+w, y+h), (255, 255, 00), 2) face = img face = cv2.resize(face,(224,224)) if Gender.predict(face)==1: text = "Male" else: text = "Female" cv2.putText(img, text, (x, h), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255), lineType=cv2.LINE_AA)
def test_image(addr): target = ['angry','disgust','fear','happy','sad','surprise','neutral'] font = cv2.FONT_HERSHEY_SIMPLEX im = cv2.imread(addr) gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY) faces = faceCascade.detectMultiScale(gray,scaleFactor=1.1) for (x, y, w, h) in faces: cv2.rectangle(im, (x, y), (x+w, y+h), (0, 255, 0), 2,5) face_crop = im[y:y+h,x:x+w] face_crop = cv2.resize(face_crop,(48,48)) face_crop = cv2.cvtColor(face_crop, cv2.COLOR_BGR2GRAY) face_crop = face_crop.astype('float32')/255 face_crop = np.asarray(face_crop) face_crop = face_crop.reshape(1, 1,face_crop.shape[0],face_crop.shape[1]) result = target[np.argmax(model.predict(face_crop))] cv2.putText(im,result,(x,y), font, 1, (200,0,0), 3, cv2.LINE_AA) cv2.imshow('result', im) cv2.imwrite('result.jpg',im) cv2.waitKey(0)
def display_detected(self, frame, face_locs, people, confidence): """ - Display ROI's of detected faces with labels :param frame: :param face_locs: :param people : people in image classified :param confidence : recognition confidence :return: """ if not len(face_locs) == 0: # nothing detected for (top, right, bottom, left), name, conf in zip(face_locs, people, confidence): # Scale back up face locations since the frame we detected in was scaled to 1/4 size top right bottom left # string conf_4f = "%.3f" % conf peop_conf = "{} {}%".format(name, float(conf_4f) * 100) # Draw a box around the face cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2) # Draw a label with a name below the face # cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED) cv2.rectangle(frame, (left, top + 20), (right, top), (0, 0, 255), cv2.FILLED) font = cv2.FONT_HERSHEY_DUPLEX # color # cv2.putText(frame, peop_conf , (left + 6, bottom - 6), font, 0.5, (255, 255, 255), 1) cv2.putText(frame, peop_conf, (left, top + 15), font, 0.5, (255, 255, 255), 1) pass
def plotRectangles(rects,transcriptions,bgrImg,rgbCol): bgrCol=np.array(rgbCol)[[2,1,0]] res=bgrImg.copy() pts=np.empty([rects.shape[0],5,1,2]) if rects.shape[1]==4: x=rects[:,[0,2,2,0,0]] y=rects[:,[1,1,3,3,1]] elif rects.shape[1]==8: x=rects[:,[0,2,4,6,0]] y=rects[:,[1,3,5,7,1]] else: raise Exception() pts[:,:,0,0]=x pts[:,:,0,1]=y pts=pts.astype('int32') ptList=[pts[k,:,:,:] for k in range(pts.shape[0])] if not (transcriptions is None): for rectNum in range(rects.shape[0]): res=cv2.putText(res,transcriptions[rectNum],(rects[rectNum,0],rects[rectNum,1]),1,cv2.FONT_HERSHEY_PLAIN,bgrCol) res=cv2.polylines(res,ptList,False,bgrCol) return res
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_box(im, box_list, label_list, color=(0,255,0), cdict=None, form='center'): assert form == 'center' or form == 'diagonal', \ 'bounding box format not accepted: {}.'.format(form) for bbox, label in zip(box_list, label_list): if form == 'center': bbox = bbox_transform(bbox) xmin, ymin, xmax, ymax = [int(b) for b in bbox] l = label.split(':')[0] # text before "CLASS: (PROB)" if cdict and l in cdict: c = cdict[l] else: c = color # draw box cv2.rectangle(im, (xmin, ymin), (xmax, ymax), c, 1) # draw label font = cv2.FONT_HERSHEY_SIMPLEX cv2.putText(im, label, (xmin, ymax), font, 0.3, c, 1)
def add_text(img, text, text_top, image_scale): """ Args: img (numpy array of shape (width, height, 3): input image text (str): text to add to image text_top (int): location of top text to add image_scale (float): image resize scale Summary: Add display text to a frame. Returns: Next available location of top text (allows for chaining this function) """ cv2.putText( img=img, text=text, org=(0, text_top), fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=0.15 * image_scale, color=(255, 255, 255)) return text_top + int(5 * image_scale)
def save_all_detection(im_array, detections, imdb_classes=None, thresh=0.7): """ save all detections in one image with result.png :param im_array: [b=1 c h w] in rgb :param detections: [ numpy.ndarray([[x1 y1 x2 y2 score]]) for j in classes ] :param imdb_classes: list of names in imdb :param thresh: threshold for valid detections :return: """ import random im = image_processing.transform_inverse(im_array, config.PIXEL_MEANS) im = im[:, :, ::-1].copy() # back to b,g,r for j in range(1, len(imdb_classes)): color = (255*random.random(), 255*random.random(), 255*random.random()) # generate a random color dets = detections[j] for i in range(dets.shape[0]): bbox = dets[i, :4] score = dets[i, -1] if score > thresh: cv2.rectangle(im, (int(round(bbox[0])), int(round(bbox[1]))), (int(round(bbox[2])), int(round(bbox[3]))), color, 2) cv2.putText(im, '%s'%imdb_classes[j], (bbox[0], bbox[1]), cv2.FONT_HERSHEY_SIMPLEX, 1.0, color, 2) cv2.imwrite("result.jpg", im)
def draw_markers(img,markers): for m in markers: centroid = np.array(m['centroid'],dtype=np.float32) origin = np.array(m['verts'][0],dtype=np.float32) hat = np.array([[[0,0],[0,1],[.5,1.25],[1,1],[1,0]]],dtype=np.float32) hat = cv2.perspectiveTransform(hat,m_marker_to_screen(m)) if m['id_confidence']>.9: cv2.polylines(img,np.int0(hat),color = (0,0,255),isClosed=True) else: cv2.polylines(img,np.int0(hat),color = (0,255,0),isClosed=True) # cv2.polylines(img,np.int0(centroid),color = (255,255,int(255*m['id_confidence'])),isClosed=True,thickness=2) m_str = 'id: {:d}'.format(m['id']) org = origin.copy() # cv2.rectangle(img, tuple(np.int0(org+(-5,-13))[0,:]), tuple(np.int0(org+(100,30))[0,:]),color=(0,0,0),thickness=-1) cv2.putText(img,m_str,tuple(np.int0(org)[0,:]),fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=0.4, color=(0,0,255)) if 'id_confidence' in m: m_str = 'idc: {:.3f}'.format(m['id_confidence']) org += (0, 12) cv2.putText(img,m_str,tuple(np.int0(org)[0,:]),fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=0.4, color=(0,0,255)) if 'loc_confidence' in m: m_str = 'locc: {:.3f}'.format(m['loc_confidence']) org += (0, 12 ) cv2.putText(img,m_str,tuple(np.int0(org)[0,:]),fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=0.4, color=(0,0,255)) if 'frames_since_true_detection' in m: m_str = 'otf: {}'.format(m['frames_since_true_detection']) org += (0, 12 ) cv2.putText(img,m_str,tuple(np.int0(org)[0,:]),fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=0.4, color=(0,0,255)) if 'opf_vel' in m: m_str = 'otf: {}'.format(m['opf_vel']) org += (0, 12 ) cv2.putText(img,m_str,tuple(np.int0(org)[0,:]),fontFace=cv2.FONT_HERSHEY_SIMPLEX, fontScale=0.4, color=(0,0,255))
def put_text(img, i, layers, y): """ Put text on canvas :param img : Canvas :param i : i-th hidden layer, notice that layers[i].name is the name of i-th hidden layer :param layers : Layers :param y : (?, y) is the center of the neuron graph of i-th hidden layer """ ############################################################ # Write your code here! # ############################################################ cv2.putText(img, layers[i].name, (12, y - 36), cv2.LINE_AA, 0.6, (0, 0, 0), 1) ############################################################ # End # ############################################################
def update(self,frame,events): self.last_frame_ts = frame.timestamp from player_methods import transparent_circle events['fixations'] = self.g_pool.fixations_by_frame[frame.index] if self.show_fixations: for f in self.g_pool.fixations_by_frame[frame.index]: x = int(f['norm_pos'][0]*self.img_size[0]) y = int((1-f['norm_pos'][1])*self.img_size[1]) transparent_circle(frame.img, (x,y), radius=f['pix_dispersion']/2, color=(.5, .2, .6, .7), thickness=-1) cv2.putText( frame.img, '{:d}'.format(f['id']), (x+20,y), cv2.FONT_HERSHEY_DUPLEX, 0.8,(255,150,100)) # cv2.putText(frame.img,'%i - %i'%(f['start_frame_index'],f['end_frame_index']),(x,y), cv2.FONT_HERSHEY_DUPLEX,0.8,(255,150,100))
def update(self,frame,events): self.last_frame_ts = frame.timestamp from player_methods import transparent_circle events['fixations'] = self.g_pool.fixations_by_frame[frame.index] if self.show_fixations: for f in self.g_pool.fixations_by_frame[frame.index]: eye_id = f['eye_id'] x = int(f['norm_pos'][0]*self.img_size[0]) y = int((1-f['norm_pos'][1])*self.img_size[1]) transparent_circle(frame.img, (x,y), radius=f['pix_dispersion']/2, color=(.5, .2, .6, .7), thickness=-1) cv2.putText( frame.img, '{:d} - eye {:d}'.format(f['id'], eye_id), (x+20,y-5+30*eye_id), cv2.FONT_HERSHEY_DUPLEX, 0.8,(255,150,100)) # cv2.putText(frame.img,'%i - %i'%(f['start_frame_index'],f['end_frame_index']),(x,y), cv2.FONT_HERSHEY_DUPLEX,0.8,(255,150,100))
def DispID(x, y, w, h, NAME, Image): # --------------------------------- THE POSITION OF THE ID BOX --------------------------------------------- Name_y_pos = y - 10 Name_X_pos = x + w/2 - (len(NAME)*7/2) if Name_X_pos < 0: Name_X_pos = 0 elif (Name_X_pos +10 + (len(NAME) * 7) > Image.shape[1]): Name_X_pos= Name_X_pos - (Name_X_pos +10 + (len(NAME) * 7) - (Image.shape[1])) if Name_y_pos < 0: Name_y_pos = Name_y_pos = y + h + 10 # ------------------------------------ THE DRAWING OF THE BOX AND ID -------------------------------------- draw_box(Image, x, y, w, h) cv2.rectangle(Image, (Name_X_pos-10, Name_y_pos-25), (Name_X_pos +10 + (len(NAME) * 7), Name_y_pos-1), (0,0,0), -2) # Draw a Black Rectangle over the face frame cv2.rectangle(Image, (Name_X_pos-10, Name_y_pos-25), (Name_X_pos +10 + (len(NAME) * 7), Name_y_pos-1), WHITE, 1) cv2.putText(Image, NAME, (Name_X_pos, Name_y_pos - 10), cv2.FONT_HERSHEY_DUPLEX, .4, WHITE) # Print the name of the ID
def DispID2(x, y, w, h, NAME, Image): # --------------------------------- THE POSITION OF THE ID BOX ------------------------------------------------- Name_y_pos = y - 40 Name_X_pos = x + w/2 - (len(NAME)*7/2) if Name_X_pos < 0: Name_X_pos = 0 elif (Name_X_pos +10 + (len(NAME) * 7) > Image.shape[1]): Name_X_pos= Name_X_pos - (Name_X_pos +10 + (len(NAME) * 7) - (Image.shape[1])) if Name_y_pos < 0: Name_y_pos = Name_y_pos = y + h + 10 # ------------------------------------ THE DRAWING OF THE BOX AND ID -------------------------------------- cv2.rectangle(Image, (Name_X_pos-10, Name_y_pos-25), (Name_X_pos +10 + (len(NAME) * 7), Name_y_pos-1), (0,0,0), -2) # Draw a Black Rectangle over the face frame cv2.rectangle(Image, (Name_X_pos-10, Name_y_pos-25), (Name_X_pos +10 + (len(NAME) * 7), Name_y_pos-1), WHITE, 1) cv2.putText(Image, NAME, (Name_X_pos, Name_y_pos - 10), cv2.FONT_HERSHEY_DUPLEX, .4, WHITE) # Print the name of the ID # --------------- THIRD ID BOX ----------------------
def DispID3(x, y, w, h, NAME, Image): # --------------------------------- THE POSITION OF THE ID BOX ------------------------------------------------- Name_y_pos = y - 70 Name_X_pos = x + w/2 - (len(NAME)*7/2) if Name_X_pos < 0: Name_X_pos = 0 elif (Name_X_pos +10 + (len(NAME) * 7) > Image.shape[1]): Name_X_pos= Name_X_pos - (Name_X_pos +10 + (len(NAME) * 7) - (Image.shape[1])) if Name_y_pos < 0: Name_y_pos = Name_y_pos = y + h + 10 # ------------------------------------ THE DRAWING OF THE BOX AND ID -------------------------------------- cv2.rectangle(Image, (Name_X_pos-10, Name_y_pos-25), (Name_X_pos +10 + (len(NAME) * 7), Name_y_pos-1), (0,0,0), -2) # Draw a Black Rectangle over the face frame cv2.rectangle(Image, (Name_X_pos-10, Name_y_pos-25), (Name_X_pos +10 + (len(NAME) * 7), Name_y_pos-1), WHITE, 1) cv2.putText(Image, NAME, (Name_X_pos, Name_y_pos - 10), cv2.FONT_HERSHEY_DUPLEX, .4, WHITE) # Print the name of the ID
def vis_detections(im, class_name, dets, thresh=0.5): """Draw detected bounding boxes.""" inds = np.where(dets[:, -1] >= thresh)[0] if len(inds) == 0: return for i in inds: bbox = dets[i, :4] score = dets[i, -1] #Create Rectangle and Text using OpenCV #print ('ClassName:', class_name, 'bbox:', bbox, 'score:' ,score) #Draw the Rectangle cv2.rectangle(im, (bbox[0], bbox[1]), (bbox[2], bbox[3]), (0, 255, 0), 3) #Draw the Text cv2.putText(im, class_name + ' ' + str(score), (bbox[0], bbox[1]), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0, 0, 255), 2, cv2.LINE_AA) #Show Image #cv2.imshow("Detect Result", im)
def render(self, dst): t = self.t self.t += 1.0/30.0 l = 120 black = [245,245,245] white = [10,10,10] colors = [black,white] nsq = 0 x = 0 for xs in range(0,16): y = 0 for ys in range(0,9): fg = colors[nsq%2] bg = colors[(nsq+1) % 2] dst[y:y+l,x:x+l] = bg cv2.putText(dst, "%s" % nsq, (x+l/4, y+2*l/3), cv2.FONT_HERSHEY_PLAIN, 3, [0,0,255], thickness = 2, lineType=cv2.LINE_AA) y+=l nsq+=1 x+=l
def get_label_colortable(n_labels, shape): if cv2 is None: raise RuntimeError('get_label_colortable requires OpenCV (cv2)') rows, cols = shape if rows * cols < n_labels: raise ValueError cmap = label_colormap(n_labels) table = np.zeros((rows * cols, 50, 50, 3), dtype=np.uint8) for lbl_id, color in enumerate(cmap): color_uint8 = (color * 255).astype(np.uint8) table[lbl_id, :, :] = color_uint8 text = '{:<2}'.format(lbl_id) cv2.putText(table[lbl_id], text, (5, 35), cv2.cv.CV_FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 3) table = table.reshape(rows, cols, 50, 50, 3) table = table.transpose(0, 2, 1, 3, 4) table = table.reshape(rows * 50, cols * 50, 3) return table # ----------------------------------------------------------------------------- # Evaluation # -----------------------------------------------------------------------------
def click_and_crop(event, x, y, flags, param): global bbs, x_upper, id if event == cv2.EVENT_LBUTTONDOWN: if x_upper: bbs.append([x,y,0,0, 0,0,0,0]) else: bbs[-1][4] = x bbs[-1][5] = y elif event == cv2.EVENT_LBUTTONUP: if x_upper: bbs[-1][2] = abs(x - bbs[-1][0]) bbs[-1][3] = abs(y - bbs[-1][1]) bbs[-1][0] = min(x, bbs[-1][0]) bbs[-1][1] = min(y, bbs[-1][1]) cv2.rectangle(image, (bbs[-1][0],bbs[-1][1]), (bbs[-1][0]+bbs[-1][2],bbs[-1][1]+bbs[-1][3]), (0,0,255), 2) #cv2.putText(image, 'Upper %d' % id, (bbs[-1][0],bbs[-1][1]), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0,0,255)) else: bbs[-1][6] = abs(x - bbs[-1][4]) bbs[-1][7] = abs(y - bbs[-1][5]) bbs[-1][4] = min(x, bbs[-1][4]) bbs[-1][5] = min(y, bbs[-1][5]) cv2.rectangle(image, (bbs[-1][4],bbs[-1][5]), (bbs[-1][4]+bbs[-1][6],bbs[-1][5]+bbs[-1][7]), (0,255,0), 2) cv2.putText(image, 'Body %d' % id, (bbs[-1][4],bbs[-1][5]), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (0,255,0)) cv2.imshow("image", image) x_upper = not x_upper
def draw_result(out, im_scale, clss, bbox, nms_thresh, conf): CV_AA = 16 for cls_id in range(1, 21): _cls = clss[:, cls_id][:, np.newaxis] _bbx = bbox[:, cls_id * 4: (cls_id + 1) * 4] dets = np.hstack((_bbx, _cls)) keep = nms(dets, nms_thresh) dets = dets[keep, :] inds = np.where(dets[:, -1] >= conf)[0] for i in inds: x1, y1, x2, y2 = map(int, dets[i, :4]) cv.rectangle(out, (x1, y1), (x2, y2), (0, 0, 255), 2, CV_AA) ret, baseline = cv.getTextSize( CLASSES[cls_id], cv.FONT_HERSHEY_SIMPLEX, 0.8, 1) cv.rectangle(out, (x1, y2 - ret[1] - baseline), (x1 + ret[0], y2), (0, 0, 255), -1) cv.putText(out, CLASSES[cls_id], (x1, y2 - baseline), cv.FONT_HERSHEY_SIMPLEX, 0.8, (255, 255, 255), 1, CV_AA) return out
def detect(imgfile): origimg = cv2.imread(imgfile) img = preprocess(origimg) img = img.astype(np.float32) img = img.transpose((2, 0, 1)) net.blobs['data'].data[...] = img out = net.forward() box, conf, cls = postprocess(origimg, out) for i in range(len(box)): p1 = (box[i][0], box[i][1]) p2 = (box[i][2], box[i][3]) cv2.rectangle(origimg, p1, p2, (0,255,0)) p3 = (max(p1[0], 15), max(p1[1], 15)) title = "%s:%.2f" % (CLASSES[int(cls[i])], conf[i]) cv2.putText(origimg, title, p3, cv2.FONT_ITALIC, 0.6, (0, 255, 0), 1) cv2.imshow("SSD", origimg) k = cv2.waitKey(0) & 0xff #Exit if ESC pressed if k == 27 : return False return True
def draw_rects(img, rects, color): """ ????????????? :param img: :param rects: :param color: :return: """ for x, y, w, h in rects: face = img[x:x+w,y:y+h] face = cv2.resize(face,(224,224)) if gender.predict(face)==1: text = "Male" else: text = "Female" cv2.rectangle(img, (x, y), (w, h), color, 2) cv2.putText(img, text, (x, h), cv2.FONT_HERSHEY_SIMPLEX, 2.0, (255, 255, 255), lineType=cv2.LINE_AA)
def draw_detection(im, bboxes, scores, cls_inds, cfg, thr=0.3): # draw image colors = cfg.colors labels = cfg.label_names imgcv = np.copy(im) h, w, _ = imgcv.shape for i, box in enumerate(bboxes): if scores[i] < thr: continue cls_indx = cls_inds[i] thick = int((h + w) / 300) cv2.rectangle(imgcv, (box[0], box[1]), (box[2], box[3]), colors[cls_indx], thick) mess = '%s: %.3f' % (labels[cls_indx], scores[i]) cv2.putText(imgcv, mess, (box[0], box[1] - 12), 0, 1e-3 * h, colors[cls_indx], thick // 3) return imgcv
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 _draw_boxes_to_image(im, res): colors = [(86, 0, 240), (173, 225, 61), (54, 137, 255),\ (151, 0, 255), (243, 223, 48), (0, 117, 255),\ (58, 184, 14), (86, 67, 140), (121, 82, 6),\ (174, 29, 128), (115, 154, 81), (86, 255, 234)] font = cv2.FONT_HERSHEY_SIMPLEX image = np.copy(im) cnt = 0 for ind, r in enumerate(res): if r['dets'] is None: continue dets = r['dets'] for i in range(0, dets.shape[0]): (x1, y1, x2, y2, score) = dets[i, :] cv2.rectangle(image, (int(x1), int(y1)), (int(x2), int(y2)), colors[ind % len(colors)], 2) text = '{:s} {:.2f}'.format(r['class'], score) cv2.putText(image, text, (x1, y1), font, 0.6, colors[ind % len(colors)], 1) cnt = (cnt + 1) return image
def _draw_on_image(img, objs, class_sets_dict): colors = [(86, 0, 240), (173, 225, 61), (54, 137, 255),\ (151, 0, 255), (243, 223, 48), (0, 117, 255),\ (58, 184, 14), (86, 67, 140), (121, 82, 6),\ (174, 29, 128), (115, 154, 81), (86, 255, 234)] font = cv2.FONT_HERSHEY_SIMPLEX for ind, obj in enumerate(objs): if obj['box'] is None: continue x1, y1, x2, y2 = obj['box'].astype(int) cls_id = class_sets_dict[obj['class']] if obj['class'] == 'dontcare': cv2.rectangle(img, (int(x1), int(y1)), (int(x2), int(y2)), (255, 0, 0), 1) continue cv2.rectangle(img, (int(x1), int(y1)), (int(x2), int(y2)), colors[cls_id % len(colors)], 1) text = '{:s}*|'.format(obj['class'][:3]) if obj['difficult'] == 1 else '{:s}|'.format(obj['class'][:3]) text += '{:.1f}|'.format(obj['truncation']) text += str(obj['occlusion']) cv2.putText(img, text, (x1-2, y2-2), font, 0.5, (255, 0, 255), 1) return img
def my_draw_box(im, box_list, label_list, color=(0,255,0), cdict=None, label_placement='bottom'): assert label_placement == 'bottom' or label_placement == 'top', \ 'label_placement format not accepted: {}.'.format(label_placement) for bbox, label in zip(box_list, label_list): xmin, ymin, xmax, ymax = [int(b) for b in bbox] l = label.split(':')[0] # text before "CLASS: (PROB)" if cdict and l in cdict: c = cdict[l] else: c = color # draw box cv2.rectangle(im, (xmin, ymin), (xmax, ymax), c, 1) # draw label font = cv2.FONT_HERSHEY_SIMPLEX if label_placement == 'bottom': cv2.putText(im, label, (xmin, ymax), font, 0.3, c, 1) else: cv2.putText(im, label, (xmin, ymin), font, 0.3, c, 1)
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 patText(s0): '''make text pattern''' arr = np.zeros((s0,s0), dtype=np.uint8) s = int(round(s0/100.)) p1 = 0 pp1 = int(round(s0/10.)) for pos0 in np.linspace(0,s0,10): cv2.putText(arr, 'helloworld', (p1,int(round(pos0))), cv2.FONT_HERSHEY_COMPLEX_SMALL, fontScale=s, color=255, thickness=s, lineType=cv2.LINE_AA ) if p1: p1 = 0 else: p1 = pp1 return arr.astype(float)
def display_shape(): global shape if shape == 0: cv2.putText(obj, 'Off', (50, 250), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 255, 255), 2) elif shape == 1: cv2.putText(obj, 'Pencil', (50, 250), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 255, 255), 2) elif shape == 2: cv2.putText(obj, 'Brush', (50, 250), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 255, 255), 2) elif shape == 3: cv2.putText(obj, 'Eraser', (50, 250), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 255, 255), 2) elif shape == 4: cv2.putText(obj, 'Line', (50, 250), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 255, 255), 2) elif shape == 5: cv2.putText(obj, 'Rectangle', (50, 250), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 255, 255), 2) elif shape == 6: cv2.putText(obj, 'Circle', (50, 250), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 255, 255), 2)
def bboxes_draw_on_img(img, classes, scores, bboxes, colors, thickness=2): shape = img.shape for i in range(bboxes.shape[0]): bbox = bboxes[i] color = colors[classes[i]] # Draw bounding box... p1 = (int(bbox[0] * shape[0]), int(bbox[1] * shape[1])) p2 = (int(bbox[2] * shape[0]), int(bbox[3] * shape[1])) cv2.rectangle(img, p1[::-1], p2[::-1], color, thickness) # Draw text... s = '%s/%.3f' % (classes[i], scores[i]) p1 = (p1[0]-5, p1[1]) cv2.putText(img, s, p1[::-1], cv2.FONT_HERSHEY_DUPLEX, 0.4, color, 1) # =========================================================================== # # Matplotlib show... # =========================================================================== #
def drawAxis(camera_parameters, markers, frame): axis = np.float32([[1,0,0], [0,1,0], [0,0,1]]).reshape(-1,3) mtx, dist = camera_parameters.camera_matrix, camera_parameters.dist_coeff for marker in markers: rvec, tvec = marker.rvec, marker.tvec imgpts, jac = cv2.projectPoints(axis, rvec, tvec, mtx, dist) corners = marker.corners corner = tuple(corners[0].ravel()) cv2.line(frame, corner, tuple(imgpts[0].ravel()), (0,0,255), 2) cv2.line(frame, corner, tuple(imgpts[1].ravel()), (0,255,0), 2) cv2.line(frame, corner, tuple(imgpts[2].ravel()), (255,0,0), 2) font = cv2.FONT_HERSHEY_SIMPLEX cv2.putText(frame, 'X', tuple(imgpts[0].ravel()), font, 0.5, (0,0,255), 2, cv2.LINE_AA) cv2.putText(frame, 'Y', tuple(imgpts[1].ravel()), font, 0.5, (0,255,0), 2, cv2.LINE_AA) cv2.putText(frame, 'Z', tuple(imgpts[2].ravel()), font, 0.5, (255,0,0), 2, cv2.LINE_AA)
def process_image(self, inImg): (self.frame_width, self.frame_height) = (112, 92) frame = cv2.flip(inImg,1,0) grayImg = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) cropped = cv2.resize(grayImg, (grayImg.shape[1] / self.size, grayImg.shape[0] / self.size)) faces = self.haar_cascade.detectMultiScale(cropped) faces = sorted(faces, key=lambda x: x[3]) if faces: face_i = faces[0] x = face_i[0] * self.size y = face_i[1] * self.size w = face_i[2] * self.size h = face_i[3] * self.size face = grayImg[y:y + h, x:x + w] face_resize = cv2.resize(face, (self.frame_width, self.frame_height)) img_no = sorted([int(fn[:fn.find('.')]) for fn in os.listdir(self.path) if fn[0]!='.' ]+[0])[-1] + 1 if self.count % self.cp_rate == 0: cv2.imwrite('%s/%s.png' % (self.path, img_no), face_resize) print "Captured Img: ", self.count/self.cp_rate + 1 cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3) cv2.putText(frame, self.face_name, (x - 10, y - 10), cv2.FONT_HERSHEY_PLAIN, 1,(0, 255, 0)) self.count += 1 return frame
def _renderResultOnImage(self, result, arr): """ Draws boxes and text representing each face's emotion. """ import operator, cv2 img = cv2.cvtColor(cv2.imdecode(arr, -1), cv2.COLOR_BGR2RGB) for currFace in result: faceRectangle = currFace['faceRectangle'] cv2.rectangle(img,(faceRectangle['left'],faceRectangle['top']), (faceRectangle['left']+faceRectangle['width'], faceRectangle['top'] + faceRectangle['height']), color = (255,0,0), thickness = 5) for currFace in result: faceRectangle = currFace['faceRectangle'] currEmotion = max(iter(currFace['scores'].items()), key=operator.itemgetter(1))[0] textToWrite = '{0}'.format(currEmotion) cv2.putText(img, textToWrite, (faceRectangle['left'],faceRectangle['top']-10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0), 1) return img
def lipSegment(self, img): # self.t1 = cv2.getTickCount() lipHull = self.dlib_obj.get_landmarks(img) cv2.drawContours(img, lipHull, -1, (255, 0, 0), 2) (x, y), (MA, ma), angle = cv2.fitEllipse(lipHull) a = ma/2 b = MA/2 eccentricity = sqrt(pow(a, 2)-pow(b, 2)) eccentricity = round(eccentricity/a, 2) cv2.putText(img, 'E = '+str(round(eccentricity, 3)), (10, 350), self.font, 1, (255, 0, 0), 1) if(eccentricity < 0.9): self.flags.cmd = 'b' else: self.flags.cmd = 'f' if angle < 80: self.flags.cmd = 'l' elif angle > 100: self.flags.cmd = 'r' cv2.putText(img, 'Cmd = ' + self.flags.cmd, (10, 300), self.font, 1, (0, 0, 255), 1, 16) # self.t2 = cv2.getTickCount() # print "Time = ", (self.t2-self.t1)/cv2.getTickFrequency() return img
def photoRead(filename): frame = cv2.imread(filename) FaceArray = getFaceArray(frame) for r in FaceArray: img2 = cv2.rectangle(frame, (r[0], r[1]), (r[2], r[3]), (0, 255, 0), 3) img3 = frame[r[1]:r[3], r[0]:r[2]] # ????????????? feature = Tools.get_feature(img3) name = readFace(feature) font = cv2.FONT_HERSHEY_SIMPLEX img2 = cv2.putText(img2, name, (r[1], r[3]), font, 1, (255, 255, 255), 2) cv2.imshow('frame', frame) cv2.waitKey(0)
def start(): cap = cv2.VideoCapture(0) while(True): # Capture frame-by-frame ret, frame = cap.read() FaceArray=getFaceArray(frame) img2=frame for r in FaceArray : img2=cv2.rectangle(frame, (r[0], r[1]), (r[2], r[3]), (0, 255, 0), 3) img3 = frame[r[1]:r[3], r[0]:r[2]] # ????????????? feature=Tools.get_feature(img3) name=readFace(feature) font=cv2.FONT_HERSHEY_SIMPLEX img2= cv2.putText(img2,name,(r[1],r[3]), font, 1,(255,255,255),2) cv2.imshow('frame',img2) if cv2.waitKey(1) & 0xFF == ord('q'): break
def renderResultOnImage( result, img ): """Display the obtained results onto the input image""" for currFace in result: faceRectangle = currFace['faceRectangle'] cv2.rectangle( img,(faceRectangle['left'],faceRectangle['top']), (faceRectangle['left']+faceRectangle['width'], faceRectangle['top'] + faceRectangle['height']), color = (255,0,0), thickness = 5 ) for currFace in result: faceRectangle = currFace['faceRectangle'] currEmotion = max(currFace['scores'].items(), key=operator.itemgetter(1))[0] textToWrite = "%s" % ( currEmotion ) cv2.putText( img, textToWrite, (faceRectangle['left'],faceRectangle['top']-10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0), 1 ) # img = os.path.expanduser('~/Development/sentiEdu/learning/confusedImgs/4.jpg')
def vis_detections(im, class_name, dets, thresh=0.5): """Draw detected bounding boxes.""" inds = np.where(dets[:, -1] >= thresh)[0] if len(inds) == 0: return l_bboxes = [] for i in inds: bbox = dets[i, :4] score = dets[i, -1] print ('Det: (x_min,y_min,W,H) = ({},{},{},{}), class_name = {:s}, score = {:.3f}').format( int(bbox[0]),int(bbox[1]),int(bbox[2]-bbox[0]),int(bbox[3]-bbox[1]),class_name,score) cv2.rectangle(im, (bbox[0], bbox[3]),(bbox[2],bbox[1]), (0,255,0),2) cv2.putText(im,'{:s}:{:.3f}'.format(class_name, score), (int(bbox[0]), int(bbox[1]) - 3), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,255,0),2) l_bboxes.append({'x_min':int(bbox[0]),'y_min':int(bbox[1]),'x_max':bbox[2],'y_max':bbox[3],'cls':class_name,'score':score}) return l_bboxes
def draw_on_detected(frame, rects, timestamp): # Draw the bounding box on the frame for (x, y, w, h) in rects: cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2) # draw the text and timestamp on the frame ts = timestamp.strftime("%A %d %B %Y %I:%M:%S%p") cv2.putText(frame, "Status: Open", (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2) cv2.putText(frame, ts, (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1) # write the image to temporary file # t = TempImage() # print('File saved at' + str(t.path)) # cv2.imwrite(t.path, frame) # analyze # pi_surveillance_analyze.analyze(t.path)
def archive_with_items(self): """ Ecrit dans le dossier d'archive la frame complète avec des carrés dessinés autour des visages détectés """ logging.info("Archive l'image avec les items trouvés...") # Dessine un carré autour de chaque item for f in self.items: x, y, w, h = f #[ v for v in f ] cv2.rectangle(self.frame, (x,y), (x+w,y+h), (0,255,0), 3) # Ajoute la date et l'heure à l'image cv2.putText(self.frame, datetime.datetime.now().strftime("%c"), (5, 25), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0,0,0), 3) # On affiche l'image qui va être archivée dans une fenêtre if self.debug: cv2.imshow("preview", self.frame) cv2.waitKey() # Ecriture du fichier archive_full_name = "{0}_full.jpg".format(self.images_prefix) logging.info("Archive file is : '{0}'".format(archive_full_name)) cv2.imwrite(os.path.join(self.archive_folder, archive_full_name), self.frame)
def annotate(self, frame): text = "Frame rate: %.1f" % self.frameRate textColor = (0,255,0) font = cv2.FONT_HERSHEY_SIMPLEX size = 0.5 thickness = 2 textSize = cv2.getTextSize(text, font, size, thickness) height = textSize[1] location = (0,frame.shape[0] - 4*height) cv2.putText(frame, text, location, font, size, textColor, thickness=thickness) text = "Detection rate: %.1f" % self.detectionRate location = (0,frame.shape[0] - height) cv2.putText(frame, text, location, font, size, textColor, thickness=thickness)
