diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..a8c2003 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,5 @@ +{ + "python-envs.defaultEnvManager": "ms-python.python:conda", + "python-envs.defaultPackageManager": "ms-python.python:conda", + "python-envs.pythonProjects": [] +} \ No newline at end of file diff --git a/RAFT_test.py b/RAFT_test.py index 5473f68..b06d9c8 100644 --- a/RAFT_test.py +++ b/RAFT_test.py @@ -96,7 +96,7 @@ def compute_dense_optical_flow_simple(prev_gray, curr_gray): def main_simple(): # Initialize camera - sensor = orisys.Sensor('s1.mp4', config_name="prototype", cal_path= "./config/cal.npy", isstitch=True, cuda=True, verbose=True) + sensor = orisys.Sensor('s1.mp4', config_name="./config/prototype_of3.json", cal_path= "./config/cal.npy", isstitch=True, cuda=True, verbose=True) model = setup_simple_raft() device = "cuda" if torch.cuda.is_available() else "cpu" print(f"Using device: {device}") @@ -118,6 +118,8 @@ def main_simple(): sensor.get_img() frame = sensor.img.copy() frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) + if prev_gray is None: + prev_gray = frame.copy gray = frame # Compute optical flow if prev_gray is not None: @@ -202,7 +204,7 @@ def main_simple(): # cv2.imshow('Grayscale', gray) cv2.imshow('Optical Flow', arrows) - prev_gray = gray.copy() + # prev_gray = gray.copy() #步骤 3.5: 键盘控制 key = cv2.waitKey(1) & 0xFF diff --git a/example3_plot_data.py b/example3_plot_data.py new file mode 100644 index 0000000..473ec8b --- /dev/null +++ b/example3_plot_data.py @@ -0,0 +1,188 @@ +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 + +def create_plot(): + p1 = win.addPlot(title="法相力") + p1.setLabel('bottom', '时间', units='s') + win.nextRow() + p2 = win.addPlot(title="切向力 X") + p2.setLabel('bottom', '时间', units='s') + win.nextRow() + p3 = win.addPlot(title="切向力 Y") + p3.setLabel('bottom', '时间', units='s') + plot_af = p1.plot(pen='k') + plot_tfx = p2.plot(pen='k') + plot_tfy = p3.plot(pen='k') + 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])) + +# 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', 'w') +pg.setConfigOption('foreground', 'k') +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(0, config_name="./config/prototype_of3.json", cal_path= "./config/dd01a_98.npy", isstitch=True, cuda=False, verbose=True) + + start_time = time.time() + is_save = False + frame_count = 0 + writer = None + while True: + sensor1.get_img() # 提取并拼接复眼图像 + + if is_save and writer is not None and sensor1.frame is not None: + frame_count += 1 + save_img = sensor1.frame + + # 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) + + sensor1.compute_deformation() # 计算形变和分解 + # 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 = sensor1.read_info(sensor1.info.FPS, sensor1.info.FNORMAL, sensor1.info.FSHEARX, sensor1.info.FSHEARY, sensor1.info.VRAW) + print(fps,fn,fx,fy) + # 显示向量场 + arrows = orisys.util.draw_arrows(sensor1.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) + + # 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 + + key = cv2.waitKey(1) + if key & 0xFF == ord("q"): + print("\n 停止程序") + break + if key == ord("s"): + save_path = f"./data/pulse_test.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: + # 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] + 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 + else: + print("No frame available to determine video dimensions") + 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 + + sensor1.disconnect() # 断开传感器连接 + + + +if __name__ == '__main__': + main()