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UPDATE Vision

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This commit is contained in:
HJW
2024-09-10 16:09:11 +08:00
parent 529c9e4082
commit 9593fa1b90
4 changed files with 45 additions and 33 deletions
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20
Vision/camera_coordinate_dete.py
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@ -24,15 +24,18 @@ class Detection:
self.camera_rvc = camera()
self.model = yolov8_segment()
self.model.load_model(model_path, device)
if self.camera_rvc.caminit_isok == True:
print("RVC X Camera is opened!")
else:
print("RVC X Camera is not opened!")
# if self.camera_rvc.caminit_isok == True:
# print("RVC X Camera is opened!")
# else:
# print("RVC X Camera is not opened!")
def get_position(self, Point_isVision=True):
def get_position(self, Point_isVision=False, first_depth=False):
""
'''
:param api: None
:param api:
Point_isVision： 点云可视化
first_depth： 按Z轴深度返回坐标及向量
:return: ret , img, (x,y,z), (nx, ny, nz)
'''
ret, img, pm = self.camera_rvc.get_img_and_point_map() # 拍照，获取图像及
@ -110,6 +113,9 @@ class Detection:
pm_seg = select_point.reshape(-1, 3)
pm_seg = pm_seg[~np.isnan(pm_seg).all(axis=-1), :] # 剔除 nan
# cv2.imshow('result', piont_result)
if pm_seg.size < 300:
print("分割出的点云数量较少，无法拟合平面！")
continue
'''
拟合平面，计算法向量
@ -157,7 +163,7 @@ class Detection:
seg_point.append(pm_seg)
cv2.polylines(img, [box], True, (0, 255, 0), 2)
_idx = find_position(Depth_Z, RegionalArea, 100,True)
_idx = find_position(Depth_Z, RegionalArea, 100, first_depth)
if _idx == None:
return 1, img, None, None

54
Vision/camera_coordinate_dete_img.py
View File

@ -13,15 +13,15 @@ import cv2
import open3d as o3d
from Vision.tool.CameraRVC import camera
from Vision.yolo.yolov8_pt_seg import yolov8_segment
from Vision.tool.utils import find_position
class Detection:
def __init__(self):
model_path = './pt_model/best.pt'
device = 'cpu'
img_path = './pt_model/test0824.png'
point_path = './pt_model/test0824.xyz'
img_path = './pt_model/test0910.png'
point_path = './pt_model/test0910.xyz'
self.model = yolov8_segment()
self.model.load_model(model_path, device)
self.img = cv2.imread(img_path)
@ -39,6 +39,7 @@ class Detection:
ret = 1
img = self.img
pm = self.point
if ret == 1:
flag, det_cpu, dst_img, masks, category_names = self.model.model_inference(img, 0)
if flag == 1:
@ -55,7 +56,7 @@ class Detection:
pm2[:, 2] = pm2[:, 2] + 0.25
pcd2 = o3d.geometry.PointCloud()
pcd2.points = o3d.utility.Vector3dVector(pm2)
#o3d.visualization.draw_geometries([pcd2])
# o3d.visualization.draw_geometries([pcd2])
for i, item in enumerate(det_cpu):
@ -87,7 +88,7 @@ class Detection:
ret, binary = cv2.threshold(imgray, 10, 255, 0)
# 阈值 二进制图像
# cv2.imshow('bin',binary)
# cv2.waitKey(0)
# cv2.waitKey(1)
contours, hierarchy = cv2.findContours(binary, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
# all_piont_list = contours_in(contours)
# print(len(all_piont_list))
@ -106,15 +107,15 @@ class Detection:
pixel_point2 = cv2.findNonZero(mask_inside)
# result = np.zeros_like(color_image)
select_point = []
for t in range(pixel_point2.shape[0]):
select_point.append(pm[pixel_point2[t][0][1] + box_y1, pixel_point2[t][0][0]+ box_x1])
for i in range(pixel_point2.shape[0]):
select_point.append(pm[pixel_point2[i][0][1] + box_y1, pixel_point2[i][0][0] + box_x1])
select_point = np.array(select_point)
pm_seg = select_point.reshape(-1, 3)
pm_seg = pm_seg[~np.isnan(pm_seg).all(axis=-1), :] # 剔除 nan
# cv2.imshow('result', piont_result)
if pm_seg.size < 300:
print("分割出的点云数量较少，无法拟合平面！")
continue
'''
拟合平面，计算法向量
'''
@ -161,23 +162,26 @@ class Detection:
seg_point.append(pm_seg)
cv2.polylines(img, [box], True, (0, 255, 0), 2)
min_value = min(Depth_Z) # 求深度最小值
min_idx = Depth_Z.index(min_value) # 求最小值对应索引
cv2.circle(img, (uv[min_idx][0], uv[min_idx][1]), 30, (0, 0, 255), 20) # 标出中心点
_idx = find_position(Depth_Z, RegionalArea, 100, True)
if Point_isVision == True:
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(seg_point[min_idx])
plane_model, inliers = pcd.segment_plane(distance_threshold=0.01,
ransac_n=5,
num_iterations=5000)
inlier_cloud = pcd.select_by_index(inliers) # 点云可视化
inlier_cloud.paint_uniform_color([1.0, 0, 0])
outlier_cloud = pcd.select_by_index(inliers, invert=True)
outlier_cloud.paint_uniform_color([0, 1, 0])
o3d.visualization.draw_geometries([inlier_cloud, outlier_cloud, pcd2])
if _idx == None:
return 1, img, None, None
else:
cv2.circle(img, (uv[_idx][0], uv[_idx][1]), 30, (255, 0, 0), 20) # 标出中心点
return 1, img, xyz[min_idx], nx_ny_nz[min_idx]
if Point_isVision == True:
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(seg_point[_idx])
plane_model, inliers = pcd.segment_plane(distance_threshold=0.01,
ransac_n=5,
num_iterations=5000)
inlier_cloud = pcd.select_by_index(inliers) # 点云可视化
inlier_cloud.paint_uniform_color([1.0, 0, 0])
outlier_cloud = pcd.select_by_index(inliers, invert=True)
outlier_cloud.paint_uniform_color([0, 1, 0])
o3d.visualization.draw_geometries([inlier_cloud, outlier_cloud, pcd2])
return 1, img, xyz[_idx], nx_ny_nz[_idx]
else:
return 1, img, None, None

2
Vision/camera_coordinate_dete_test.py
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@ -5,7 +5,7 @@
# @Author : hjw
# @File : camera_coordinate_dete_test.py.py
'''
from camera_coordinate_dete import Detection
from camera_coordinate_dete_img import Detection
import cv2
detection = Detection()

2
requirements
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@ -22,3 +22,5 @@ PyRVC=1.10.0
torch=1.13.1
torchvision=0.14.1
ultralytics=8.2.86
openvino=2024.0.0
lapx=0.5.10