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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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32
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 = []
@ -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))
@ -133,6 +122,10 @@ 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)
''' '''
@ -186,7 +179,7 @@ class Detection:
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()
@ -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)
''' '''