Python cv2.WINDOW_AUTOSIZE Examples
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code examples of cv2.WINDOW_AUTOSIZE().
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Example #1
Source File: vachat.py From The-chat-room with MIT License | 10 votes |
def run(self): print("VEDIO server starts...") self.sock.bind(self.ADDR) self.sock.listen(1) conn, addr = self.sock.accept() print("remote VEDIO client success connected...") data = "".encode("utf-8") payload_size = struct.calcsize("L") cv2.namedWindow('Remote', cv2.WINDOW_AUTOSIZE) while True: while len(data) < payload_size: data += conn.recv(81920) packed_size = data[:payload_size] data = data[payload_size:] msg_size = struct.unpack("L", packed_size)[0] while len(data) < msg_size: data += conn.recv(81920) zframe_data = data[:msg_size] data = data[msg_size:] frame_data = zlib.decompress(zframe_data) frame = pickle.loads(frame_data) cv2.imshow('Remote', frame) if cv2.waitKey(1) & 0xFF == 27: break
Example #2
Source File: SudokuExtractor.py From SolveSudoku with MIT License | 7 votes |
def parse_grid(path): original = cv2.imread(path, cv2.IMREAD_GRAYSCALE) processed = pre_process_image(original) # cv2.namedWindow('processed',cv2.WINDOW_AUTOSIZE) # processed_img = cv2.resize(processed, (500, 500)) # Resize image # cv2.imshow('processed', processed_img) corners = find_corners_of_largest_polygon(processed) cropped = crop_and_warp(original, corners) # cv2.namedWindow('cropped',cv2.WINDOW_AUTOSIZE) # cropped_img = cv2.resize(cropped, (500, 500)) # Resize image # cv2.imshow('cropped', cropped_img) squares = infer_grid(cropped) # print(squares) digits = get_digits(cropped, squares, 28) # print(digits) final_image = show_digits(digits) return final_image
Example #3
Source File: RtspClient.py From ReolinkCameraAPI with GNU General Public License v3.0 | 6 votes |
def preview(self): """ Blocking function. Opens OpenCV window to display stream. """ self.connect() win_name = 'RTSP' cv2.namedWindow(win_name, cv2.WINDOW_AUTOSIZE) cv2.moveWindow(win_name, 20, 20) while True: cv2.imshow(win_name, self.get_frame()) # if self._latest is not None: # cv2.imshow(win_name,self._latest) if cv2.waitKey(25) & 0xFF == ord('q'): break cv2.waitKey() cv2.destroyAllWindows() cv2.waitKey()
Example #4
Source File: emulator.py From fathom with Apache License 2.0 | 6 votes |
def __init__(self, rom_name, vis,frameskip=1,windowname='preview'): self.ale = ALEInterface() self.max_frames_per_episode = self.ale.getInt("max_num_frames_per_episode"); self.ale.setInt("random_seed",123) self.ale.setInt("frame_skip",frameskip) romfile = str(ROM_PATH)+str(rom_name) if not os.path.exists(romfile): print('No ROM file found at "'+romfile+'".\nAdjust ROM_PATH or double-check the filt exists.') self.ale.loadROM(romfile) self.legal_actions = self.ale.getMinimalActionSet() self.action_map = dict() self.windowname = windowname for i in range(len(self.legal_actions)): self.action_map[self.legal_actions[i]] = i # print(self.legal_actions) self.screen_width,self.screen_height = self.ale.getScreenDims() print("width/height: " +str(self.screen_width) + "/" + str(self.screen_height)) self.vis = vis if vis: cv2.startWindowThread() cv2.namedWindow(self.windowname, flags=cv2.WINDOW_AUTOSIZE) # permit manual resizing
Example #5
Source File: vis_utils.py From PVN3D with MIT License | 6 votes |
def cv2_show_image(window_name, image, size_wh=None, location_xy=None): """Helper function for specifying window size and location when displaying images with cv2. Args: window_name: str window name image: ndarray image to display size_wh: window size (w, h) location_xy: window location (x, y) """ if size_wh is not None: cv2.namedWindow(window_name, cv2.WINDOW_KEEPRATIO | cv2.WINDOW_GUI_NORMAL) cv2.resizeWindow(window_name, *size_wh) else: cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE) if location_xy is not None: cv2.moveWindow(window_name, *location_xy) cv2.imshow(window_name, image)
Example #6
Source File: drawers.py From ethoscope with GNU General Public License v3.0 | 6 votes |
def __init__(self, video_out=None, draw_frames=True, video_out_fourcc="DIVX", video_out_fps=2): """ A template class to annotate and save the processed frames. It can also save the annotated frames in a video file and/or display them in a new window. The :meth:`~ethoscope.drawers.drawers.BaseDrawer._annotate_frame` abstract method defines how frames are annotated. :param video_out: The path to the output file (.avi) :type video_out: str :param draw_frames: Whether frames should be displayed on the screen (a new window will be created). :type draw_frames: bool :param video_out_fourcc: When setting ``video_out``, this defines the codec used to save the output video (see `fourcc <http://www.fourcc.org/codecs.php>`_) :type video_out_fourcc: str :param video_out_fps: When setting ``video_out``, this defines the output fps. typically, the same as the input fps. :type video_out_fps: float """ self._video_out = video_out self._draw_frames= draw_frames self._video_writer = None self._window_name = "ethoscope_" + str(os.getpid()) self._video_out_fourcc = video_out_fourcc self._video_out_fps = video_out_fps if draw_frames: cv2.namedWindow(self._window_name, cv2.WINDOW_AUTOSIZE) self._last_drawn_frame = None
Example #7
Source File: vis_utils.py From ip_basic with MIT License | 6 votes |
def cv2_show_image(window_name, image, size_wh=None, location_xy=None): """Helper function for specifying window size and location when displaying images with cv2. Args: window_name: str window name image: ndarray image to display size_wh: window size (w, h) location_xy: window location (x, y) """ if size_wh is not None: cv2.namedWindow(window_name, cv2.WINDOW_KEEPRATIO | cv2.WINDOW_GUI_NORMAL) cv2.resizeWindow(window_name, *size_wh) else: cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE) if location_xy is not None: cv2.moveWindow(window_name, *location_xy) cv2.imshow(window_name, image)
Example #8
Source File: simple-camera.py From ai-smarthome with BSD 2-Clause "Simplified" License | 6 votes |
def show_camera(): # To flip the image, modify the flip_method parameter (0 and 2 are the most common) print(gstreamer_pipeline(flip_method=0)) cap = cv2.VideoCapture(gstreamer_pipeline(flip_method=0), cv2.CAP_GSTREAMER) if cap.isOpened(): window_handle = cv2.namedWindow('CSI Camera', cv2.WINDOW_AUTOSIZE) # Window while cv2.getWindowProperty('CSI Camera',0) >= 0: ret_val, img = cap.read(); cv2.imshow('CSI Camera',img) # This also acts as keyCode = cv2.waitKey(30) & 0xff # Stop the program on the ESC key if keyCode == 27: break cap.release() cv2.destroyAllWindows() else: print('Unable to open camera')
Example #9
Source File: ffmpegstream.py From rtsp with MIT License | 5 votes |
def preview(self): """ Blocking function. Opens OpenCV window to display stream. """ win_name = 'Camera' cv2.namedWindow(win_name, cv2.WINDOW_AUTOSIZE) cv2.moveWindow(win_name,20,20) self.open() while(self.isOpened()): cv2.imshow(win_name,self._stream.read()[1]) if cv2.waitKey(25) & 0xFF == ord('q'): break cv2.waitKey() cv2.destroyAllWindows() cv2.waitKey()
Example #10
Source File: ffmpegstream.py From rtsp with MIT License | 5 votes |
def preview(self): """ Blocking function. Opens OpenCV window to display stream. """ win_name = 'RTSP' cv2.namedWindow(win_name, cv2.WINDOW_AUTOSIZE) cv2.moveWindow(win_name,20,20) while(self.isOpened()): cv2.imshow(win_name,self.read(raw=True)) if cv2.waitKey(25) & 0xFF == ord('q'): break cv2.waitKey() cv2.destroyAllWindows() cv2.waitKey()
Example #11
Source File: vis_utils.py From monopsr with MIT License | 5 votes |
def cv2_imshow(window_name, image, size_wh=None, row_col=None, location_xy=None): """Helper function for specifying window size and location when displaying images with cv2 Args: window_name (string): Window title image: image to display size_wh: resize window Recommended sizes for 1920x1080 screen: 2 col: (930, 280) 3 col: (620, 187) 4 col: (465, 140) row_col: Row and column to show images like subplots location_xy: location of window """ if size_wh is not None: cv2.namedWindow(window_name, cv2.WINDOW_KEEPRATIO | cv2.WINDOW_GUI_NORMAL) cv2.resizeWindow(window_name, *size_wh) else: cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE | cv2.WINDOW_GUI_NORMAL) if row_col is not None: start_x_offset = 60 start_y_offset = 25 y_offset = 28 subplot_row = row_col[0] subplot_col = row_col[1] location_xy = (start_x_offset + subplot_col * size_wh[0], start_y_offset + subplot_row * size_wh[1] + subplot_row * y_offset) if location_xy is not None: cv2.moveWindow(window_name, *location_xy) cv2.imshow(window_name, image)
Example #12
Source File: start_face_recon_app.py From Smart-Surveillance-System-using-Raspberry-Pi with GNU General Public License v3.0 | 5 votes |
def add_person(people_folder, shape): """ Funtion to add pictures of a person """ person_name = input('What is the name of the new person: ').lower() folder = people_folder + person_name if not os.path.exists(folder): input("I will now take 20 pictures. Press ENTER when ready.") os.mkdir(folder) video = VideoCamera() detector = FaceDetector('face_recognition_system/frontal_face.xml') counter = 1 timer = 0 cv2.namedWindow('Video Feed', cv2.WINDOW_AUTOSIZE) cv2.namedWindow('Saved Face', cv2.WINDOW_NORMAL) while counter < 21: frame = video.get_frame() face_coord = detector.detect(frame) if len(face_coord): frame, face_img = get_images(frame, face_coord, shape) # save a face every second, we start from an offset '5' because # the first frame of the camera gets very high intensity # readings. if timer % 100 == 5: cv2.imwrite(folder + '/' + str(counter) + '.jpg', face_img[0]) print ('Images Saved:' + str(counter)) counter += 1 cv2.imshow('Saved Face', face_img[0]) cv2.imshow('Video Feed', frame) cv2.waitKey(50) timer += 5 else: print ("This name already exists.") sys.exit()
Example #13
Source File: opencv_image_viewer.py From dm2gym with MIT License | 5 votes |
def __init__(self, *, escape_to_exit=False): """Construct the viewing window""" self._escape_to_exit = escape_to_exit self._window_name = str(uuid.uuid4()) cv2.namedWindow(self._window_name, cv2.WINDOW_AUTOSIZE) self._isopen = True
Example #14
Source File: demo.py From YOLOv3 with MIT License | 5 votes |
def detect_video(video, yolo, all_classes): """Use yolo v3 to detect video. # Argument: video: video file. yolo: YOLO, yolo model. all_classes: all classes name. """ video_path = os.path.join("videos", "test", video) camera = cv2.VideoCapture(video_path) cv2.namedWindow("detection", cv2.WINDOW_AUTOSIZE) # Prepare for saving the detected video sz = (int(camera.get(cv2.CAP_PROP_FRAME_WIDTH)), int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT))) fourcc = cv2.VideoWriter_fourcc(*'mpeg') vout = cv2.VideoWriter() vout.open(os.path.join("videos", "res", video), fourcc, 20, sz, True) while True: res, frame = camera.read() if not res: break image = detect_image(frame, yolo, all_classes) cv2.imshow("detection", image) # Save the video frame by frame vout.write(image) if cv2.waitKey(110) & 0xff == 27: break vout.release() camera.release()
Example #15
Source File: ColorFilter.py From ImageProcessingProjects with MIT License | 5 votes |
def showImage(title, image): cv.namedWindow(title, cv.WINDOW_AUTOSIZE) cv.imshow(title, image) cv.waitKey(0)
Example #16
Source File: ImageManipulation.py From ImageProcessingProjects with MIT License | 5 votes |
def thresholdGrayImage(): cv.namedWindow('Thresholding', cv.WINDOW_AUTOSIZE) cv.createTrackbar('Threshold', 'Thresholding',128, 255, sliderCallBack) cv.waitKey(0)
Example #17
Source File: ImageManipulation.py From ImageProcessingProjects with MIT License | 5 votes |
def showImage(title, image): cv.namedWindow(title, cv.WINDOW_AUTOSIZE) cv.imshow(title, image) cv.waitKey(0) # works with gray images
Example #18
Source File: jetson_live_object_detection.py From jetson_nano_detection_and_tracking with GNU Lesser General Public License v2.1 | 5 votes |
def start(self): print ("Starting Live object detection, may take a few minutes to initialize...") self.camera.startStreaming() self.detector.initializeSession() if not self.camera.isOpened(): print ("Camera has failed to open") exit(-1) elif self.debug: cv2.namedWindow("Jetson Live Detection", cv2.WINDOW_AUTOSIZE) while True: curr_time = time.time() img = self.camera.getFrame() scores, boxes, classes, num_detections = self.detector.detect(img) if self.debug: self._visualizeDetections(img, scores, boxes, classes, num_detections) print ("Debug: Running at: " + str(1.0/(time.time() - curr_time)) + " Hz.") if cv2.waitKey(1) == ord('q'): break # throttle to rate capture_duration = time.time() - curr_time sleep_time = self.rate - capture_duration if sleep_time > 0: time.sleep(sleep_time) cv2.destroyAllWindows() self.camera.__del__() self.detector.__del__() print ("Exiting...") return
Example #19
Source File: display_video.py From image-processing-pipeline with MIT License | 5 votes |
def __init__(self, src, window_name=None, org=None): self.src = src self.window_name = window_name if window_name else src cv2.startWindowThread() cv2.namedWindow(self.window_name, cv2.WINDOW_AUTOSIZE) if org: # Set the window position x, y = org cv2.moveWindow(self.window_name, x, y) super(DisplayVideo, self).__init__()
Example #20
Source File: display_video.py From detectron2-pipeline with MIT License | 5 votes |
def __init__(self, src, window_name=None, org=None): self.src = src self.window_name = window_name if window_name else src cv2.startWindowThread() cv2.namedWindow(self.window_name, cv2.WINDOW_AUTOSIZE) if org: # Set the window position x, y = org cv2.moveWindow(self.window_name, x, y) super().__init__()
Example #21
Source File: ocr.py From pokr with MIT License | 5 votes |
def __init__(self, debug=False): self.debug = debug if self.debug: cv2.namedWindow("Stream", cv2.WINDOW_AUTOSIZE) self.tile_map = self.make_tilemap('firered_tiles.png') self.tile_text = self.make_tile_text('firered_tiles.txt') self.ocr_engine = video.OCREngine(self.tile_map, self.tile_text)
Example #22
Source File: drawing.py From PyIntroduction with MIT License | 5 votes |
def drawingDemo(): img = emptyImage() # 太さ2の直線描画 drawLine(img, (10, 10), (200, 200), (0, 0, 255), 2) # 太さに-1を指定すると,塗りつぶしになる drawCircle(img, (300, 100), 80, (0, 255, 0), -1) # 中と外を両方描画 drawRectangle(img, (10, 210), (210, 350), (100, 100, 0), -1) drawRectangle(img, (10, 210), (210, 350), (255, 0, 0), 3) # 楕円の描画 drawElipse(img, (450, 100), (30, 80), 0, 0, 360, (0, 100, 100), -1) # ポリゴンの描画 pts = np.array([[(250, 240), (270, 280), (350, 320), (500, 300), (450, 230), (350, 210)]], dtype=np.int32) drawPolylines(img, pts, True, (255, 100, 100), 5) # テキストの描画 drawText(img, 'OpenCV', (20, 450), font_types[0], 4, (200, 200, 200), 2) cv2.namedWindow('DrawingDemo', cv2.WINDOW_AUTOSIZE) cv2.imshow('DrawingDemo', img) cv2.waitKey(0) cv2.destroyAllWindows()
Example #23
Source File: fer_demo.py From Efficient-Facial-Feature-Learning-with-Wide-Ensemble-based-Convolutional-Neural-Networks with MIT License | 5 votes |
def __init__(self, window_name=_DEFAULT_WINDOW_NAME, screen_size=_DEFAULT_SCREEN_SIZE_ID, display_individual_classification=_DEFAULT_DISPLAY_INDIVIDUAL_CLASSIFICATION, display_graph_ensemble=_DEFAULT_DISPLAY_GRAPH_ENSEMBLE): """ Initialize GUI of the FER demo. :param window_name: (string) The name of the window :param screen_size: ((int, int)) Tuple of int values for width and height, respectively. """ # Screen components self._fer = None self._input_image = None self._background = None self._plot_arousal = [] self._plot_valence = [] # Screen self._window_name = window_name self._screen_size = screen_size - 1 self._width, self._height = FERDemo._SCREEN_SIZE[self._screen_size] self._display_individual_classification = display_individual_classification self._display_graph_ensemble = display_graph_ensemble # Container parameters self._container_width, self._container_height = (int(self._width // 2), int(self._height)) self._container_center_position = np.array([self._container_width // 2, self._container_height // 2], dtype=np.int) self._input_container = None self._output_container = None self._input_container_initial_position = np.array([0, 0], dtype=np.int) self._output_container_initial_position = np.array([0, self._width // 2], dtype=np.int) # Output blocks self._output_block_height = (self._container_height // FERDemo._BLOCK_NUM_BLOCKS) self._output_block_height_ensemble = self._container_height self._output_block_width = self._container_width # Screen initialization self._draw_background() self._screen = self._get_container(0, 0, self._height, self._width) self._blank_screen() cv2.namedWindow(self._window_name, cv2.WINDOW_AUTOSIZE)
Example #24
Source File: Utils.py From pix2code with Apache License 2.0 | 5 votes |
def show(image): import cv2 cv2.namedWindow("view", cv2.WINDOW_AUTOSIZE) cv2.imshow("view", image) cv2.waitKey(0) cv2.destroyWindow("view")
Example #25
Source File: opencv_windows_management.py From OpenCV-Python-Tutorial with MIT License | 5 votes |
def add(self, name, image, weight=1): ''' 权重,越高,图片显示越大 :return: ''' cv2.namedWindow(name, flags=cv2.WINDOW_AUTOSIZE) window = Window(name, image, weight) self.windows[name] = window # self.windows[name] = image
Example #26
Source File: match_template.py From OpenCV-Python-Tutorial with MIT License | 5 votes |
def main(argv): if (len(sys.argv) < 3): print 'Not enough parameters' print 'Usage:\nmatch_template_demo.py <image_name> <template_name> [<mask_name>]' return -1 ## [load_image] global img global templ img = cv2.imread(sys.argv[1], cv2.IMREAD_COLOR) templ = cv2.imread(sys.argv[2], cv2.IMREAD_COLOR) if (len(sys.argv) > 3): global use_mask use_mask = True global mask mask = cv2.imread( sys.argv[3], cv2.IMREAD_COLOR ) if ((img is None) or (templ is None) or (use_mask and (mask is None))): print 'Can\'t read one of the images' return -1 ## [load_image] ## [create_windows] cv2.namedWindow( image_window, cv2.WINDOW_AUTOSIZE ) cv2.namedWindow( result_window, cv2.WINDOW_AUTOSIZE ) ## [create_windows] ## [create_trackbar] trackbar_label = 'Method: \n 0: SQDIFF \n 1: SQDIFF NORMED \n 2: TM CCORR \n 3: TM CCORR NORMED \n 4: TM COEFF \n 5: TM COEFF NORMED' cv2.createTrackbar( trackbar_label, image_window, match_method, max_Trackbar, MatchingMethod ) ## [create_trackbar] MatchingMethod(match_method) ## [wait_key] cv2.waitKey(0) return 0 ## [wait_key]
Example #27
Source File: ball_tracker.py From SunFounder_PiCar-V with GNU General Public License v2.0 | 4 votes |
def find_blob() : radius = 0 # Load input image _, bgr_image = img.read() orig_image = bgr_image bgr_image = cv2.medianBlur(bgr_image, 3) # Convert input image to HSV hsv_image = cv2.cvtColor(bgr_image, cv2.COLOR_BGR2HSV) # Threshold the HSV image, keep only the red pixels lower_red_hue_range = cv2.inRange(hsv_image, (0, 100, 100), (10, 255, 255)) upper_red_hue_range = cv2.inRange(hsv_image, (160, 100, 100), (179, 255, 255)) # Combine the above two images red_hue_image = cv2.addWeighted(lower_red_hue_range, 1.0, upper_red_hue_range, 1.0, 0.0) red_hue_image = cv2.GaussianBlur(red_hue_image, (9, 9), 2, 2) # Use the Hough transform to detect circles in the combined threshold image circles = cv2.HoughCircles(red_hue_image, cv2.HOUGH_GRADIENT, 1, 120, 100, 20, 10, 0) circles = np.uint16(np.around(circles)) # Loop over all detected circles and outline them on the original image all_r = np.array([]) # print("circles: %s"%circles) if circles is not None: try: for i in circles[0,:]: # print("i: %s"%i) all_r = np.append(all_r, int(round(i[2]))) closest_ball = all_r.argmax() center=(int(round(circles[0][closest_ball][0])), int(round(circles[0][closest_ball][1]))) radius=int(round(circles[0][closest_ball][2])) if draw_circle_enable: cv2.circle(orig_image, center, radius, (0, 255, 0), 5) except IndexError: pass # print("circles: %s"%circles) # Show images if show_image_enable: cv2.namedWindow("Threshold lower image", cv2.WINDOW_AUTOSIZE) cv2.imshow("Threshold lower image", lower_red_hue_range) cv2.namedWindow("Threshold upper image", cv2.WINDOW_AUTOSIZE) cv2.imshow("Threshold upper image", upper_red_hue_range) cv2.namedWindow("Combined threshold images", cv2.WINDOW_AUTOSIZE) cv2.imshow("Combined threshold images", red_hue_image) cv2.namedWindow("Detected red circles on the input image", cv2.WINDOW_AUTOSIZE) cv2.imshow("Detected red circles on the input image", orig_image) k = cv2.waitKey(5) & 0xFF if k == 27: return (0, 0), 0 if radius > 3: return center, radius else: return (0, 0), 0
Example #28
Source File: vis.py From PINTO_model_zoo with MIT License | 4 votes |
def vis_tflite(model): interpreter = tf.lite.Interpreter(model_path=model) interpreter.allocate_tensors() input_details = interpreter.get_input_details() output_details = interpreter.get_output_details() input_size = 160 image_width = 640 image_height = 480 cam = cv2.VideoCapture(0) cam.set(cv2.CAP_PROP_FPS, 30) cam.set(cv2.CAP_PROP_FRAME_WIDTH, image_width) cam.set(cv2.CAP_PROP_FRAME_HEIGHT, image_height) window_name = "USB Camera" cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE) scalex = image_width / input_size scaley = image_height / input_size while True: start_time = time.perf_counter() ret, image = cam.read() if not ret: continue img_show = np.array(image) frame = cv2.resize(image, (input_size, input_size)) frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) frame = np.expand_dims(frame, axis=0) frame = frame.astype(np.float32) start=time.time() interpreter.set_tensor(input_details[0]['index'], frame) interpreter.invoke() tflite_res = interpreter.get_tensor(output_details[2]['index']) print('xxxx',time.time()-start) img_show=img_show.astype(np.uint8) landmark = np.array(tflite_res).reshape([-1, 2]) for _index in range(landmark.shape[0]): x_y = landmark[_index] cv2.circle(img_show, center=(int(x_y[0] * input_size * scalex), int(x_y[1] * input_size * scaley)), color=(255, 122, 122), radius=1, thickness=2) cv2.imshow('USB camera',img_show) if cv2.waitKey(1)&0xFF == ord('q'): break
Example #29
Source File: mobilenetv2ssd-async-usbcam.py From TensorflowLite-bin with Apache License 2.0 | 4 votes |
def camThread(results, frameBuffer, camera_width, camera_height, vidfps, usbcamno): global fps global detectfps global framecount global detectframecount global time1 global time2 global lastresults global cam global window_name cam = cv2.VideoCapture(usbcamno) cam.set(cv2.CAP_PROP_FPS, vidfps) cam.set(cv2.CAP_PROP_FRAME_WIDTH, camera_width) cam.set(cv2.CAP_PROP_FRAME_HEIGHT, camera_height) window_name = "USB Camera" cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE) while True: t1 = time.perf_counter() ret, color_image = cam.read() if not ret: continue if frameBuffer.full(): frameBuffer.get() frames = color_image frameBuffer.put(color_image.copy()) res = None if not results.empty(): res = results.get(False) detectframecount += 1 imdraw = overlay_on_image(frames, res, camera_width, camera_height) lastresults = res else: imdraw = overlay_on_image(frames, lastresults, camera_width, camera_height) cv2.imshow('USB Camera', imdraw) if cv2.waitKey(1)&0xFF == ord('q'): break # FPS calculation framecount += 1 if framecount >= 15: fps = "(Playback) {:.1f} FPS".format(time1/15) detectfps = "(Detection) {:.1f} FPS".format(detectframecount/time2) framecount = 0 detectframecount = 0 time1 = 0 time2 = 0 t2 = time.perf_counter() elapsedTime = t2-t1 time1 += 1/elapsedTime time2 += elapsedTime
Example #30
Source File: MobileNet-SSD-TPU-async.py From TPU-MobilenetSSD with MIT License | 4 votes |
def camThread(label, results, frameBuffer, camera_width, camera_height, vidfps, usbcamno): global fps global detectfps global framecount global detectframecount global time1 global time2 global lastresults global cam global window_name cam = cv2.VideoCapture(usbcamno) cam.set(cv2.CAP_PROP_FPS, vidfps) cam.set(cv2.CAP_PROP_FRAME_WIDTH, camera_width) cam.set(cv2.CAP_PROP_FRAME_HEIGHT, camera_height) window_name = "USB Camera" cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE) while True: t1 = time.perf_counter() ret, color_image = cam.read() if not ret: continue if frameBuffer.full(): frameBuffer.get() frames = color_image frameBuffer.put(color_image.copy()) res = None if not results.empty(): res = results.get(False) detectframecount += 1 imdraw = overlay_on_image(frames, res, label, camera_width, camera_height) lastresults = res else: imdraw = overlay_on_image(frames, lastresults, label, camera_width, camera_height) cv2.imshow('USB Camera', imdraw) if cv2.waitKey(1)&0xFF == ord('q'): break # FPS calculation framecount += 1 if framecount >= 15: fps = "(Playback) {:.1f} FPS".format(time1/15) detectfps = "(Detection) {:.1f} FPS".format(detectframecount/time2) framecount = 0 detectframecount = 0 time1 = 0 time2 = 0 t2 = time.perf_counter() elapsedTime = t2-t1 time1 += 1/elapsedTime time2 += elapsedTime