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UPDATE openvino

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This commit is contained in:
HJW
2024-09-11 14:16:15 +08:00
parent 7fab3b3ffa
commit 2b20732119
2 changed files with 160 additions and 160 deletions
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48
Vision/camera_coordinate_dete.py
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@ -15,29 +15,24 @@ from Vision.tool.CameraRVC import camera
from Vision.yolo.yolov8_pt_seg import yolov8_segment from Vision.yolo.yolov8_pt_seg import yolov8_segment
from Vision.yolo.yolov8_openvino import yolov8_segment_openvino from Vision.yolo.yolov8_openvino import yolov8_segment_openvino
from Vision.tool.utils import find_position from Vision.tool.utils import find_position
from Vision.tool.utils import class_names
import os import os
class Detection: class Detection:
def __init__(self, use_openvino_model = False): def __init__(self, use_openvino_model = False):
print(os.getcwd())
self.use_openvino_model = use_openvino_model self.use_openvino_model = use_openvino_model
if self.use_openvino_model == False: if self.use_openvino_model==False:
model_path = ''.join([os.getcwd(), '/model/pt/best.pt']) model_path = ''.join([os.getcwd(), '/model/pt/best.pt'])
device = 'cpu' device = 'cpu'
self.camera_rvc = camera()
self.model = yolov8_segment() self.model = yolov8_segment()
self.model.load_model(model_path, device) self.model.load_model(model_path, device)
else: else:
model_path = ''.join([os.getcwd(), '/model/openvino/bset.xml']) model_path = ''.join([os.getcwd(), '/model/openvino/last-0903.xml'])
device = 'CPU' device = 'CPU'
self.camera_rvc = camera()
self.model = yolov8_segment_openvino(model_path, device, conf_thres=0.3, iou_thres=0.3) self.model = yolov8_segment_openvino(model_path, device, conf_thres=0.3, iou_thres=0.3)
img_path = ''.join([os.getcwd(), '/model/data/test0910.png'])
point_path = ''.join([os.getcwd(), '/model/data/test0910.xyz'])
self.img = cv2.imread(img_path)
self.point = np.loadtxt(point_path).reshape((1080, 1440, 3))
def get_position(self, Point_isVision=True): def get_position(self, Point_isVision=True):
@ -46,16 +41,13 @@ class Detection:
:param api: None :param api: None
:return: ret , img, (x,y,z), (nx, ny, nz) :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 ret, img, pm = self.camera_rvc.get_img_and_point_map() # 拍照，获取图像及
ret = 1 if self.camera_rvc.caminit_isok == True:
img = self.img
pm = self.point
if ret == 1: if ret == 1:
if self.use_openvino_model == False: if self.use_openvino_model == False:
flag, det_cpu, dst_img, masks, category_names = self.model.model_inference(img, 0) flag, det_cpu, dst_img, masks, category_names = self.model.model_inference(img, 0)
else: else:
flag, det_cpu, scores, masks, category_names = self.model.segment_objects(img) flag, det_cpu, scores, masks, category_names = self.model.segment_objects(img)
dst_img = img
if flag == 1: if flag == 1:
xyz = [] xyz = []
nx_ny_nz = [] nx_ny_nz = []
@ -63,7 +55,7 @@ class Detection:
Depth_Z = [] Depth_Z = []
uv = [] uv = []
seg_point = [] seg_point = []
if Point_isVision == True: if Point_isVision==True:
pm2 = pm.copy() pm2 = pm.copy()
pm2 = pm2.reshape(-1, 3) pm2 = pm2.reshape(-1, 3)
pm2 = pm2[~np.isnan(pm2).all(axis=-1), :] pm2 = pm2[~np.isnan(pm2).all(axis=-1), :]
@ -76,10 +68,7 @@ class Detection:
# 画box # 画box
box_x1, box_y1, box_x2, box_y2 = item[0:4].astype(np.int32) box_x1, box_y1, box_x2, box_y2 = item[0:4].astype(np.int32)
if self.use_openvino_model == False:
label = category_names[int(item[5])] label = category_names[int(item[5])]
else:
label = class_names[int(item[4])]
rand_color = (0, 255, 255) rand_color = (0, 255, 255)
score = item[4] score = item[4]
org = (int((box_x1 + box_x2) / 2), int((box_y1 + box_y2) / 2)) org = (int((box_x1 + box_x2) / 2), int((box_y1 + box_y2) / 2))
@ -129,10 +118,14 @@ class Detection:
# result = np.zeros_like(color_image) # result = np.zeros_like(color_image)
select_point = [] select_point = []
for i in range(pixel_point2.shape[0]): 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.append(pm[pixel_point2[i][0][1]+box_y1, pixel_point2[i][0][0]+box_x1])
select_point = np.array(select_point) select_point = np.array(select_point)
pm_seg = select_point.reshape(-1, 3) pm_seg = select_point.reshape(-1, 3)
pm_seg = pm_seg[~np.isnan(pm_seg).all(axis=-1), :] # 剔除 nan pm_seg = pm_seg[~np.isnan(pm_seg).all(axis=-1), :] # 剔除 nan
if pm_seg.size<300:
print("分割点云数量较少，无法拟合平面")
continue
# cv2.imshow('result', piont_result) # cv2.imshow('result', piont_result)
''' '''
@ -144,7 +137,7 @@ class Detection:
ransac_n=5, ransac_n=5,
num_iterations=5000) num_iterations=5000)
[a, b, c, d] = plane_model [a, b, c, d] = plane_model
# print(f"Plane equation: {a:.2f}x + {b:.2f}y + {c:.2f}z + {d:.2f} = 0") #print(f"Plane equation: {a:.2f}x + {b:.2f}y + {c:.2f}z + {d:.2f} = 0")
# inlier_cloud = pcd.select_by_index(inliers) # 点云可视化 # inlier_cloud = pcd.select_by_index(inliers) # 点云可视化
# inlier_cloud.paint_uniform_color([1.0, 0, 0]) # inlier_cloud.paint_uniform_color([1.0, 0, 0])
@ -173,22 +166,22 @@ class Detection:
if np.isnan(point_x): # 点云值为无效值 if np.isnan(point_x): # 点云值为无效值
continue continue
else: else:
xyz.append([point_x * 1000, point_y * 1000, point_z * 1000]) xyz.append([point_x*1000, point_y*1000, point_z*1000])
Depth_Z.append(point_z * 1000) Depth_Z.append(point_z*1000)
nx_ny_nz.append([a, b, c]) nx_ny_nz.append([a, b, c])
RegionalArea.append(cv2.contourArea(max_contour)) RegionalArea.append(cv2.contourArea(max_contour))
uv.append([x_rotation_center, y_rotation_center]) uv.append([x_rotation_center, y_rotation_center])
seg_point.append(pm_seg) seg_point.append(pm_seg)
cv2.polylines(img, [box], True, (0, 255, 0), 2) cv2.polylines(img, [box], True, (0, 255, 0), 2)
_idx = find_position(Depth_Z, RegionalArea, 100, True) _idx = find_position(Depth_Z, RegionalArea, 100,True)
if _idx == None: if _idx == None:
return 1, img, None, None return 1, img, None, None
else: else:
cv2.circle(img, (uv[_idx][0], uv[_idx][1]), 30, (0, 0, 255), 20) # 标出中心点 cv2.circle(img, (uv[_idx][0], uv[_idx][1]), 30, (255, 0, 0), 20) # 标出中心点
if Point_isVision == True: if Point_isVision==True:
pcd = o3d.geometry.PointCloud() pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(seg_point[_idx]) pcd.points = o3d.utility.Vector3dVector(seg_point[_idx])
plane_model, inliers = pcd.segment_plane(distance_threshold=0.01, plane_model, inliers = pcd.segment_plane(distance_threshold=0.01,
@ -208,7 +201,12 @@ class Detection:
print("RVC X Camera capture failed!") print("RVC X Camera capture failed!")
return 0, None, None, None return 0, None, None, None
else:
print("RVC X Camera is not opened!")
return 0, None, None, None
def release(self): def release(self):
self.camera_rvc.release()
self.model.clear() self.model.clear()

4
Vision/camera_coordinate_dete_img.py
View File

@ -54,7 +54,6 @@ class Detection:
flag, det_cpu, dst_img, masks, category_names = self.model.model_inference(img, 0) flag, det_cpu, dst_img, masks, category_names = self.model.model_inference(img, 0)
else: else:
flag, det_cpu, scores, masks, category_names = self.model.segment_objects(img) flag, det_cpu, scores, masks, category_names = self.model.segment_objects(img)
dst_img = img
if flag == 1: if flag == 1:
xyz = [] xyz = []
nx_ny_nz = [] nx_ny_nz = []
@ -132,6 +131,9 @@ class Detection:
select_point = np.array(select_point) select_point = np.array(select_point)
pm_seg = select_point.reshape(-1, 3) pm_seg = select_point.reshape(-1, 3)
pm_seg = pm_seg[~np.isnan(pm_seg).all(axis=-1), :] # 剔除 nan pm_seg = pm_seg[~np.isnan(pm_seg).all(axis=-1), :] # 剔除 nan
if pm_seg.size < 300:
print("分割点云数量较少，无法拟合平面")
continue
# cv2.imshow('result', piont_result) # cv2.imshow('result', piont_result)
''' '''