From 5fac40207c9ee741c18c22b7c2dccb754d87b6ff Mon Sep 17 00:00:00 2001 From: ykcheung Date: Sat, 31 Jan 2026 21:28:23 +0800 Subject: [PATCH] add pulse test --- pulse_process.py | 308 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 308 insertions(+) create mode 100644 pulse_process.py diff --git a/pulse_process.py b/pulse_process.py new file mode 100644 index 0000000..4e3ebb1 --- /dev/null +++ b/pulse_process.py @@ -0,0 +1,308 @@ +import os +os.environ["OPENCV_VIDEOIO_MSMF_ENABLE_HW_TRANSFORMS"] = "0" +import cv2 +import orisys +import numpy as np +import time + +import pyqtgraph as pg +from PyQt5.QtGui import QImage + +def create_plot(): + p1 = win.addPlot(title="法相") + p1.setLabel('bottom', '时间', units='s') + win.nextRow() + p2 = win.addPlot(title="切向 X") + p2.setLabel('bottom', '时间', units='s') + win.nextRow() + p3 = win.addPlot(title="切向 Y") + p3.setLabel('bottom', '时间', units='s') + plot_af = p1.plot(pen='w') + plot_tfx = p2.plot(pen='w') + plot_tfy = p3.plot(pen='w') + return p1, p2, p3, plot_af, plot_tfx, plot_tfy + +def update(plot_af, plot_tfx, plot_tfy, data, p1, p2, p3): + # global plot_af, plot_tfx, plot_tfy, data, p1, p2, p3 + plot_af.setData(data[:,:,0]) + p1.setYRange(min(data[:,1,0]),max(data[:,1,0])) + plot_tfx.setData(data[:,:,1]) + p2.setYRange(min(data[:,1,1]),max(data[:,1,1])) + plot_tfy.setData(data[:,:,2]) + p3.setYRange(min(data[:,1,2]),max(data[:,1,2])) + +def plot_to_frame(plot_widget, width=None, height=None): + """ + Convert pyqtgraph GraphicsLayoutWidget to numpy array (BGR format for OpenCV). + + Args: + plot_widget: pyqtgraph GraphicsLayoutWidget to capture + width: Optional width for output frame (default: widget width) + height: Optional height for output frame (default: widget height) + + Returns: + np.ndarray: BGR image array (height, width, 3) ready for cv2.VideoWriter + """ + # Get the widget size + if width is None: + width = plot_widget.width() + if height is None: + height = plot_widget.height() + + # Grab the widget as a QPixmap + pixmap = plot_widget.grab() + + # Resize if needed + if pixmap.width() != width or pixmap.height() != height: + pixmap = pixmap.scaled(width, height) + + # Convert QPixmap to QImage + qimage = pixmap.toImage() + + # Convert QImage to RGB format + qimage = qimage.convertToFormat(QImage.Format_RGB888) + + # Get image dimensions + img_width = qimage.width() + img_height = qimage.height() + + # Convert QImage to numpy array + # Use constBits() to get raw bytes, then reshape + buffer = qimage.constBits() + if buffer is not None: + arr = np.frombuffer(buffer, dtype=np.uint8).reshape((img_height, img_width, 3)) + else: + # Fallback: create empty array + arr = np.zeros((img_height, img_width, 3), dtype=np.uint8) + + # Convert RGB to BGR for OpenCV + bgr = cv2.cvtColor(arr, cv2.COLOR_RGB2BGR) + + return bgr + +# 深度图 +def draw_magnitude_map(vfield, threshold=3.0, colormap=cv2.COLORMAP_JET) -> np.ndarray: + """ + Draw color map of pointwise magnitude of velocity field. + + Args: + vfield: Velocity field to visualize (2D vector field) + threshold: Minimum magnitude to display (below threshold shows as zero/blue) + colormap: OpenCV colormap to use (default: COLORMAP_JET) + + Returns: + np.ndarray: 400x400 BGR image with colored magnitude map + """ + flow_field = vfield + + # Compute magnitude at each point + magnitude = np.sqrt(flow_field[:, :, 0]**2 + flow_field[:, :, 1]**2) + + # Smooth by downsampling and interpolating back + downsample_factor = 10 + h, w = magnitude.shape + magnitude_downsampled = magnitude[::downsample_factor, ::downsample_factor] + magnitude_smoothed = cv2.resize(magnitude_downsampled, (w, h), interpolation=cv2.INTER_CUBIC) + + # Apply threshold - set below-threshold values to zero + magnitude_thresholded = magnitude_smoothed.copy() + magnitude_thresholded[magnitude_smoothed < threshold] = 0 + + # Normalize to 0-255 range + mag_min, mag_max = magnitude_thresholded.min(), magnitude_thresholded.max() + if mag_max > mag_min: + magnitude_norm = ((magnitude_thresholded - mag_min) / (mag_max - mag_min) * 255).astype(np.uint8) + else: + magnitude_norm = np.zeros_like(magnitude_thresholded, dtype=np.uint8) + + # Apply colormap + magnitude_colored = cv2.applyColorMap(magnitude_norm, colormap) + + # Resize to output size + out_img = cv2.resize(magnitude_colored, (400, 400), interpolation=cv2.INTER_CUBIC) + + return out_img + +# 实时图表 +npoints = 100 # 图表数据长度 +pg.setConfigOption('background', 'k') +pg.setConfigOption('foreground', 'w') +app = pg.mkQApp("Plotting Example") +win = pg.GraphicsLayoutWidget(show=True, title="Basic plotting examples") +win.setWindowTitle('pyqtgraph example: Plotting') +p1, p2, p3, plot_af, plot_tfx, plot_tfy = create_plot() +data = np.zeros([npoints,2,3]) +start_time = None # Will be set when sensor starts +for i in range(3): + data[:,0,i] = np.linspace(-npoints,0,npoints) + + + +def main(): + global start_time + + # 打开视频 + # sensor1 = Sensor("./s1.mp4",isstitch=True,cuda = True,verbose = True) + # 方式1: 从视频文件读取 + sensor1 = orisys.Sensor("./data/pulse_test_1.mp4", config_name="./config/prototype_of3.json", cal_path= "./config/dd01a_98.npy", isstitch=True, cuda=False, verbose=True) + + start_time = time.time() + is_save = True + frame_count = 0 + writer = None + save_path = None + + # Video writer for plot + is_save_plot = True + plot_writer = None + plot_frame_count = 0 + plot_save_path = None + + if True: + save_path = f"./data/pulse_test_arrows.mp4" + # Ensure directory exists + os.makedirs(os.path.dirname(save_path), exist_ok=True) + # Get frame dimensions from the actual frame + save_img = sensor1.frame + + # if save_img is not None: + if True: + # Convert grayscale (1 channel) to BGR (3 channels) if needed for dimension check + # temp_img = save_img.copy() + # if len(temp_img.shape) == 2 or (len(temp_img.shape) == 3 and temp_img.shape[2] == 1): + # if len(temp_img.shape) == 3: + # temp_img = temp_img.squeeze(2) + # temp_img = cv2.cvtColor(temp_img, cv2.COLOR_GRAY2BGR) + + # frame_height, frame_width = temp_img.shape[:2] + frame_height = 400 + frame_width = 400 + writer = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*'mp4v'), 30, (frame_width, frame_height)) + if writer.isOpened(): + is_save = True + print(f"Start writing to {save_path}") + else: + print(f"Failed to open video writer for {save_path}") + writer = None + + # Setup video writer for plot + plot_save_path = f"./data/pulse_test_plot.mp4" + os.makedirs(os.path.dirname(plot_save_path), exist_ok=True) + # Get plot widget dimensions + plot_width = win.width() + plot_height = win.height() + # Use fixed dimensions if widget not yet rendered + if plot_width <= 0 or plot_height <= 0: + plot_width = 800 + plot_height = 600 + + plot_writer = cv2.VideoWriter(plot_save_path, cv2.VideoWriter_fourcc(*'mp4v'), 30, (plot_width, plot_height)) + if plot_writer.isOpened(): + is_save_plot = True + print(f"Start writing plot to {plot_save_path}") + else: + print(f"Failed to open plot video writer for {plot_save_path}") + plot_writer = None + + + while True: + sensor1.get_img() # 提取并拼接复眼图像 + + + + sensor1.compute_deformation() # 计算形变和分解 + sensor1.compute_contact() + # 提取信息： + # 向量场: VRAW, VNORMAL, VSHEAR: 原始，法向，切向 + # 帧率，时间戳: FPS, TIMESTAMP + # 变形量总和: FNORMAL , FSHEARX, FSHEARY : 法向，切向（X)，切向（Y) + fps, fn, fx, fy, flow, contour, centroid, depth_map = sensor1.read_info(sensor1.info.FPS, sensor1.info.FNORMAL, sensor1.info.FSHEARX, sensor1.info.FSHEARY, sensor1.info.VRAW,sensor1.info.CONTOUR, + sensor1.info.CENTROID, + sensor1.info.DEPTH) + print(fps,fn,fx,fy) + + + # 显示触碰点和区域 # 步骤 3.2: 在图像上触碰点和区域 + white_img = np.full_like(sensor1.img, 0) + + image_with_foe = orisys.util.draw_contact(white_img, contour, centroid,region_color=(255, 255, 255)) + cv2.imshow("Contact Centroid", image_with_foe) + # 显示向量场 + + arrows = orisys.util.draw_arrows(white_img, flow, threshold=5, grid_spacing=10, arrow_scale=1.0) + cv2.imshow("Deformation", arrows) + # 显示深度图 + mag = draw_magnitude_map(flow) + cv2.imshow("Magnitude", mag) + + if is_save and writer is not None and sensor1.frame is not None: + frame_count += 1 + save_img = arrows + + # Convert grayscale (1 channel) to BGR (3 channels) if needed + if len(save_img.shape) == 2 or (len(save_img.shape) == 3 and save_img.shape[2] == 1): + if len(save_img.shape) == 3: + save_img = save_img.squeeze(2) + save_img = cv2.cvtColor(save_img, cv2.COLOR_GRAY2BGR) + + writer.write(save_img) + + # 显示图表 - 更新时间轴 + current_time = time.time() - start_time + for i in range(3): + data[:-1, 0, i] = data[1:, 0, i] # shift time data left + data[:-1, 1, i] = data[1:, 1, i] # shift force data left + data[-1, 0, :] = current_time # set current time for all plots + data[-1, 1, 0] = fn + data[-1, 1, 1] = fx + data[-1, 1, 2] = fy + update(plot_af, plot_tfx, plot_tfy, data, p1, p2, p3) # Update plot + + # Capture and save plot frame + if is_save_plot and plot_writer is not None: + plot_frame_count += 1 + # Process Qt events to ensure plot is updated + app.processEvents() + # Capture plot as frame + plot_frame = plot_to_frame(win) + plot_writer.write(plot_frame) + + key = cv2.waitKey(1) + if key & 0xFF == ord("q"): + print("\n 停止程序") + break + + if key == ord("e"): + is_save = False + if writer is not None: + writer.release() + writer = None + if save_path is not None: + print(f"Stop writing to {save_path}, total frames: {frame_count}") + else: + print(f"Stop writing, total frames: {frame_count}") + frame_count = 0 + + # Stop plot recording + is_save_plot = False + if plot_writer is not None: + plot_writer.release() + plot_writer = None + if plot_save_path is not None: + print(f"Stop writing plot to {plot_save_path}, total frames: {plot_frame_count}") + else: + print(f"Stop writing plot, total frames: {plot_frame_count}") + plot_frame_count = 0 + + sensor1.disconnect() # 断开传感器连接 + + # Clean up video writers + if writer is not None: + writer.release() + if plot_writer is not None: + plot_writer.release() + print(f"Plot video saved: {plot_save_path}, total frames: {plot_frame_count}") + + +if __name__ == '__main__': + main()