IMU校准角度归一化功能提交修改
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@ -21420,3 +21420,5 @@ frontend/src/renderer/src/services/api.js
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frontend/src/renderer/src/services/api.js
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frontend/src/renderer/src/services/api.js
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frontend/src/renderer/src/services/api.js
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frontend/src/renderer/src/services/api.js
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backend/devices/utils/config.ini
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@ -67,7 +67,6 @@ class RealIMUDevice:
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if 'head_pose_offset' in calibration:
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self.head_pose_offset = calibration['head_pose_offset']
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logger.debug(f'应用IMU校准数据: {self.head_pose_offset}')
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def apply_calibration(self, raw_data: Dict[str, Any]) -> Dict[str, Any]:
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"""应用校准:将当前姿态减去初始偏移,得到相对于初始姿态的变化量"""
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if not raw_data or 'head_pose' not in raw_data:
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@ -76,15 +75,14 @@ class RealIMUDevice:
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# 应用校准偏移
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calibrated_data = raw_data.copy()
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head_pose = raw_data['head_pose'].copy()
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angle=head_pose['rotation'] - self.head_pose_offset['rotation']
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# 减去基准值(零点偏移)
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head_pose['rotation'] = head_pose['rotation'] - self.head_pose_offset['rotation']
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head_pose['rotation'] = ((angle + 180) % 360) - 180
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head_pose['tilt'] = head_pose['tilt'] - self.head_pose_offset['tilt']
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head_pose['pitch'] = head_pose['pitch'] - self.head_pose_offset['pitch']
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calibrated_data['head_pose'] = head_pose
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return calibrated_data
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@staticmethod
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def _checksum(data: bytes) -> int:
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return sum(data[:-1]) & 0xFF
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@ -115,7 +113,7 @@ class RealIMUDevice:
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'yaw': yaw,
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'temperature': temp
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}
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# logger.debug(f'解析姿态角包: roll={roll}, pitch={pitch}, yaw={yaw}, temp={temp}')
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# print(f'解析姿态角包: roll={roll}, pitch={pitch}, yaw={yaw}, temp={temp}')
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return self.last_data
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else:
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# logger.debug(f'忽略的数据包类型: 0x{packet_type:02X}')
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@ -356,37 +354,16 @@ class IMUManager(BaseDevice):
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self.logger.info('开始IMU快速零点校准...')
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# 收集校准样本
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calibration_samples = []
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sample_count = 50 # 减少样本数量以加快校准速度
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for i in range(sample_count):
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try:
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# 读取原始数据(不应用校准)
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# 直接读取一次原始数据作为校准偏移量
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raw_data = self.imu_device.read_data(apply_calibration=False)
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if raw_data and 'head_pose' in raw_data:
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calibration_samples.append(raw_data['head_pose'])
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time.sleep(0.02) # 20ms间隔
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except Exception as e:
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self.logger.warning(f'校准样本采集失败: {e}')
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continue
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if not raw_data or 'head_pose' not in raw_data:
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return {'status': 'error', 'error': '无法读取IMU原始数据'}
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if len(calibration_samples) < sample_count * 0.7:
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return {
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'status': 'error',
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'error': f'校准样本不足: {len(calibration_samples)}/{sample_count}'
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}
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# 计算平均值作为零点偏移
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rotation_sum = sum(sample['rotation'] for sample in calibration_samples)
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tilt_sum = sum(sample['tilt'] for sample in calibration_samples)
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pitch_sum = sum(sample['pitch'] for sample in calibration_samples)
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count = len(calibration_samples)
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# 使用当前姿态作为零点偏移
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self.head_pose_offset = {
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'rotation': rotation_sum / count,
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'tilt': tilt_sum / count,
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'pitch': pitch_sum / count
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'rotation': raw_data['head_pose']['rotation'],
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'tilt': raw_data['head_pose']['tilt'],
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'pitch': raw_data['head_pose']['pitch']
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}
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# 应用校准到设备
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@ -396,8 +373,7 @@ class IMUManager(BaseDevice):
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self.logger.info(f'IMU快速校准完成: {self.head_pose_offset}')
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return {
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'status': 'success',
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'head_pose_offset': self.head_pose_offset,
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'samples_used': count
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'head_pose_offset': self.head_pose_offset
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}
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except Exception as e:
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@ -504,8 +480,8 @@ class IMUManager(BaseDevice):
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if data:
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# 缓存数据
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self.data_buffer.append(data)
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self.last_valid_data = data
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# self.data_buffer.append(data)
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# self.last_valid_data = data
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# 发送数据到前端
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if self._socketio:
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@ -29,7 +29,7 @@ depth_range_max = 1700
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[DEVICES]
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imu_device_type = real
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imu_port = COM3
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imu_port = COM8
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imu_baudrate = 9600
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pressure_device_type = real
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pressure_use_mock = False
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@ -947,7 +947,7 @@ class AppServer:
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self.logger.error(f'校准设备失败: {e}')
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return jsonify({'success': False, 'error': str(e)}), 500
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@self.app.route('/api/devices/imu/calibrate', methods=['POST'])
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@self.app.route('/api/devices/calibrate/imu', methods=['POST'])
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def calibrate_imu():
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"""校准IMU"""
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try:
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@ -1,79 +1,53 @@
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import ctypes
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import time
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import numpy as np
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from PIL import Image
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import colorsys
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# === DLL 加载 ===
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dll = ctypes.WinDLL(r"D:\BodyBalanceEvaluation\backend\dll\smitsense\SMiTSenseUsbWrapper.dll")
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def get_unique_colors(image_path):
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img = Image.open(image_path).convert("RGB")
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unique_colors = list(set(img.getdata()))
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return unique_colors
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# === DLL 函数声明 ===
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dll.SMiTSenseUsb_Init.argtypes = [ctypes.c_int]
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dll.SMiTSenseUsb_Init.restype = ctypes.c_int
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def get_representative_colors(colors, n=12):
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# 按亮度排序并均匀抽取
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def brightness(rgb):
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r, g, b = rgb
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return 0.2126*r + 0.7152*g + 0.0722*b
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dll.SMiTSenseUsb_ScanDevices.argtypes = [ctypes.POINTER(ctypes.c_int)]
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dll.SMiTSenseUsb_ScanDevices.restype = ctypes.c_int
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colors.sort(key=brightness)
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total = len(colors)
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if total <= n:
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return colors
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step = total / n
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return [colors[int(i*step)] for i in range(n)]
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dll.SMiTSenseUsb_OpenAndStart.argtypes = [
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ctypes.c_int,
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ctypes.POINTER(ctypes.c_uint16),
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ctypes.POINTER(ctypes.c_uint16)
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]
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dll.SMiTSenseUsb_OpenAndStart.restype = ctypes.c_int
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def sort_colors_by_hue(colors):
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# 转为 HSV,并按色相排序
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def rgb_to_hue(rgb):
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r, g, b = [x/255.0 for x in rgb]
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h, s, v = colorsys.rgb_to_hsv(r, g, b)
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return h
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return sorted(colors, key=rgb_to_hue)
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dll.SMiTSenseUsb_GetLatestFrame.argtypes = [
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ctypes.POINTER(ctypes.c_uint16),
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ctypes.c_int
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]
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dll.SMiTSenseUsb_GetLatestFrame.restype = ctypes.c_int
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def show_color_preview(colors, width=600, height_per_color=50):
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n = len(colors)
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height = n * height_per_color
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img = Image.new("RGB", (width, height))
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dll.SMiTSenseUsb_StopAndClose.argtypes = []
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dll.SMiTSenseUsb_StopAndClose.restype = ctypes.c_int
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for i, color in enumerate(colors):
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for y in range(i*height_per_color, (i+1)*height_per_color):
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for x in range(width):
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img.putpixel((x, y), color)
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# === 初始化设备 ===
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ret = dll.SMiTSenseUsb_Init(0)
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if ret != 0:
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raise RuntimeError(f"Init failed: {ret}")
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img.show()
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count = ctypes.c_int()
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ret = dll.SMiTSenseUsb_ScanDevices(ctypes.byref(count))
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if ret != 0 or count.value == 0:
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raise RuntimeError("No devices found")
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if __name__ == "__main__":
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image_path = r"D:\项目资料\技术文档资料\中康项目资料\11.png"
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# 打开设备
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rows = ctypes.c_uint16()
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cols = ctypes.c_uint16()
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ret = dll.SMiTSenseUsb_OpenAndStart(0, ctypes.byref(rows), ctypes.byref(cols))
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if ret != 0:
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raise RuntimeError("OpenAndStart failed")
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colors = get_unique_colors(image_path)
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rep_colors = get_representative_colors(colors, 12)
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sorted_colors = sort_colors_by_hue(rep_colors)
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rows_val, cols_val = rows.value, cols.value
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frame_size = rows_val * cols_val
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buf_type = ctypes.c_uint16 * frame_size
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buf = buf_type()
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print("12 个代表性颜色(按彩虹顺序):")
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for i, color in enumerate(sorted_colors, 1):
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print(f"{i}: {color}")
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# 创建一个 NumPy 数组视图,复用内存
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data_array = np.ctypeslib.as_array(buf).reshape((rows_val, cols_val))
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print(f"设备已打开: {rows_val}x{cols_val}")
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try:
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while True:
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ret = dll.SMiTSenseUsb_GetLatestFrame(buf, frame_size)
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time.sleep(1)
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# while True:
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# ret = dll.SMiTSenseUsb_GetLatestFrame(buf, frame_size)
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# if ret == 0:
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# # data_array 已经复用缓冲区内存,每次直接访问即可
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# # 例如打印最大值和前5行前5列的数据
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# print("最大压力值:", data_array.max())
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# print("前5x5数据:\n", data_array[:5, :5])
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# else:
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# print("读取数据帧失败")
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# time.sleep(1) # 每秒读取一帧
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except KeyboardInterrupt:
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print("退出中...")
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finally:
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dll.SMiTSenseUsb_StopAndClose()
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print("设备已关闭")
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show_color_preview(sorted_colors)
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@ -59,7 +59,7 @@ def parse_packet(data):
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# else:
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# return f"未知包类型: {packet_type:#04x}"
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def read_imu(port='COM6', baudrate=9600):
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def read_imu(port='COM8', baudrate=9600):
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ser = serial.Serial(port, baudrate, timeout=1)
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buffer = bytearray()
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94
backend/tests/test44femtobolt.py
Normal file
94
backend/tests/test44femtobolt.py
Normal file
@ -0,0 +1,94 @@
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import os
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib.colors import ListedColormap
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import pykinect_azure as pykinect
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class FemtoBoltContourViewer:
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def __init__(self, depth_min=900, depth_max=1100):
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self.depth_min = depth_min
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self.depth_max = depth_max
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# 自定义离散彩虹色,层次明显
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colors = [
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'darkblue', 'blue', 'cyan', 'lime', 'yellow',
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'orange', 'red', 'darkred'
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]
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self.cmap = ListedColormap(colors)
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self.device_handle = None
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self.pykinect = None
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self.config = None
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def _load_sdk(self):
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"""加载并初始化 FemtoBolt SDK"""
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base_dir = os.path.dirname(os.path.abspath(__file__))
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dll_path = os.path.join(base_dir, "..", "dll", "femtobolt", "bin", "k4a.dll")
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self.pykinect = pykinect
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self.pykinect.initialize_libraries(track_body=False, module_k4a_path=dll_path)
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def _configure_device(self):
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"""配置 FemtoBolt 深度相机"""
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self.config = self.pykinect.default_configuration
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self.config.depth_mode = self.pykinect.K4A_DEPTH_MODE_NFOV_UNBINNED
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self.config.camera_fps = self.pykinect.K4A_FRAMES_PER_SECOND_15
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self.config.synchronized_images_only = False
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self.config.color_resolution = 0
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self.device_handle = self.pykinect.start_device(config=self.config)
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def run(self):
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self._load_sdk()
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self._configure_device()
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plt.ion() # 打开交互模式
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fig, ax = plt.subplots(figsize=(7, 7))
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print("FemtoBolt 深度相机启动成功,关闭窗口或 Ctrl+C 退出")
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# 设置离散等高线层次
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levels = np.linspace(self.depth_min, self.depth_max, len(self.cmap.colors) + 1)
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try:
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while plt.fignum_exists(fig.number): # 窗口存在才继续
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capture = self.device_handle.update()
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if capture is None:
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continue
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ret, depth_image = capture.get_depth_image()
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if not ret or depth_image is None:
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continue
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depth = depth_image.astype(np.uint16)
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# 限制深度范围
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depth[depth > self.depth_max] = 0
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depth[depth < self.depth_min] = 0
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depth = depth[0:350, 0:350]
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# 屏蔽无效值
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depth_masked = np.ma.masked_equal(depth, 0)
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# 背景灰色
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background = np.ones_like(depth) * 0.5
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# 绘制
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ax.clear()
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ax.imshow(background, origin='lower', cmap='gray', alpha=0.3)
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ax.grid(True, which='both', axis='both', color='white',
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linestyle='--', linewidth=1, zorder=0)
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ax.contourf(depth_masked, levels=levels, cmap=self.cmap,
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vmin=self.depth_min, vmax=self.depth_max,
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origin='upper', zorder=2)
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plt.pause(0.05)
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except KeyboardInterrupt:
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print("检测到退出信号,结束程序")
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finally:
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if self.device_handle:
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self.device_handle.stop()
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self.device_handle.close()
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plt.close(fig)
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if __name__ == "__main__":
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viewer = FemtoBoltContourViewer(depth_min=900, depth_max=1100)
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viewer.run()
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