add pulse test

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()