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UPDATE Vision box：bug

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This commit is contained in:
HJW
2024-10-09 15:55:29 +08:00
parent 0b34eaca53
commit b5ca028199
2 changed files with 34 additions and 5 deletions
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20
Vision/camera_coordinate_dete.py
View File

@ -63,10 +63,11 @@ class Detection:
self.model = yolov8_segment_openvino(model_path, device, conf_thres=0.3, iou_thres=0.3)
def get_position(self, Point_isVision=False, save_img_point=0, Height_reduce = 30, width_reduce = 30):
def get_position(self, Point_isVision=False, Box_isPoint=True, save_img_point=0, Height_reduce = 30, width_reduce = 30):
"""
检测料袋相关信息
:param Point_isVision: 点云可视化
:param Box_isPoint: True 返回点云值； False 返回box相机坐标
:param save_img_point: 0不保存 ; 1保存原图 ;2保存处理后的图 ; 3保存点云和原图；4 保存点云和处理后的图
:param Height_reduce: 检测框的高内缩像素
:param width_reduce: 检测框的宽内缩像素
@ -237,7 +238,13 @@ class Detection:
box[1][0][1], box[1][0][0] = out_bounds_dete(pm.shape[0], pm.shape[1], box[1][0][1], box[1][0][0])
box[2][0][1], box[2][0][0] = out_bounds_dete(pm.shape[0], pm.shape[1], box[2][0][1], box[2][0][0])
box[3][0][1], box[3][0][0] = out_bounds_dete(pm.shape[0], pm.shape[1], box[3][0][1], box[3][0][0])
if Box_isPoint == True:
box_point_x1, box_point_y1, box_point_z1 = remove_nan_mean_value(pm, box[0][0][1], box[0][0][0])
box_point_x2, box_point_y2, box_point_z2 = remove_nan_mean_value(pm, box[1][0][1], box[1][0][0])
box_point_x3, box_point_y3, box_point_z3 = remove_nan_mean_value(pm, box[2][0][1], box[2][0][0])
box_point_x4, box_point_y4, box_point_z4 = remove_nan_mean_value(pm, box[3][0][1], box[3][0][0])
else:
pass
x_rotation_center = int((box[0][0][0] + box[1][0][0] + box[2][0][0] + box[3][0][0]) / 4)
y_rotation_center = int((box[0][0][1] + box[1][0][1] + box[2][0][1] + box[3][0][1]) / 4)
point_x, point_y, point_z = remove_nan_mean_value(pm, y_rotation_center, x_rotation_center)
@ -245,7 +252,14 @@ class Detection:
if np.isnan(point_x): # 点云值为无效值
continue
else:
box_list.append(box)
if Box_isPoint == True:
box_list.append(
[[box_point_x1, box_point_y1, box_point_z1],
[box_point_x2, box_point_y2, box_point_z2],
[box_point_x3, box_point_y3, box_point_z3],
[box_point_x4, box_point_y4, box_point_z4]])
else:
box_list.append(box)
if self.cameraType=='RVC':
xyz.append([point_x*1000, point_y*1000, point_z*1000])
Depth_Z.append(point_z*1000)

19
Vision/camera_coordinate_dete_img.py
View File

@ -45,10 +45,11 @@ class Detection:
pass
def get_position(self, Point_isVision=False, save_img_point=0, seg_distance_threshold = 0.01, Height_reduce = 30, width_reduce = 30):
def get_position(self, Point_isVision=False, Box_isPoint=True, save_img_point=0, seg_distance_threshold = 0.01, Height_reduce = 30, width_reduce = 30):
"""
检测料袋相关信息
:param Point_isVision: 点云可视化
:param Box_isPoint: True 返回点云值； False 返回box相机坐标
:param save_img_point: 0不保存 ; 1保存原图 ;2保存处理后的图 ; 3保存点云和原图；4 保存点云和处理后的图
:param Height_reduce: 检测框的高内缩像素
:param width_reduce: 检测框的宽内缩像素
@ -223,6 +224,13 @@ class Detection:
box[1][0][1], box[1][0][0] = out_bounds_dete(pm.shape[0], pm.shape[1], box[1][0][1], box[1][0][0])
box[2][0][1], box[2][0][0] = out_bounds_dete(pm.shape[0], pm.shape[1], box[2][0][1], box[2][0][0])
box[3][0][1], box[3][0][0] = out_bounds_dete(pm.shape[0], pm.shape[1], box[3][0][1], box[3][0][0])
if Box_isPoint == True:
box_point_x1, box_point_y1, box_point_z1 = remove_nan_mean_value(pm, box[0][0][1], box[0][0][0])
box_point_x2, box_point_y2, box_point_z2 = remove_nan_mean_value(pm, box[1][0][1], box[1][0][0])
box_point_x3, box_point_y3, box_point_z3 = remove_nan_mean_value(pm, box[2][0][1], box[2][0][0])
box_point_x4, box_point_y4, box_point_z4 = remove_nan_mean_value(pm, box[3][0][1], box[3][0][0])
else:
pass
x_rotation_center = int((box[0][0][0] + box[1][0][0] + box[2][0][0] + box[3][0][0]) / 4)
y_rotation_center = int((box[0][0][1] + box[1][0][1] + box[2][0][1] + box[3][0][1]) / 4)
@ -231,7 +239,14 @@ class Detection:
if np.isnan(point_x): # 点云值为无效值
continue
else:
box_list.append(box)
if Box_isPoint == True:
box_list.append(
[[box_point_x1, box_point_y1, box_point_z1],
[box_point_x2, box_point_y2, box_point_z2],
[box_point_x3, box_point_y3, box_point_z3],
[box_point_x4, box_point_y4, box_point_z4]])
else:
box_list.append(box)
Depth_Z.append(point_z * 1000)
nx_ny_nz.append([a, b, c])
RegionalArea.append(cv2.contourArea(max_contour))