UPDATE openvino
This commit is contained in:
@ -15,29 +15,24 @@ from Vision.tool.CameraRVC import camera
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from Vision.yolo.yolov8_pt_seg import yolov8_segment
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from Vision.yolo.yolov8_openvino import yolov8_segment_openvino
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from Vision.tool.utils import find_position
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from Vision.tool.utils import class_names
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import os
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class Detection:
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def __init__(self, use_openvino_model = False):
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print(os.getcwd())
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self.use_openvino_model = use_openvino_model
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if self.use_openvino_model==False:
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model_path = ''.join([os.getcwd(), '/model/pt/best.pt'])
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device = 'cpu'
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self.camera_rvc = camera()
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self.model = yolov8_segment()
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self.model.load_model(model_path, device)
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else:
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model_path = ''.join([os.getcwd(), '/model/openvino/bset.xml'])
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model_path = ''.join([os.getcwd(), '/model/openvino/last-0903.xml'])
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device = 'CPU'
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self.camera_rvc = camera()
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self.model = yolov8_segment_openvino(model_path, device, conf_thres=0.3, iou_thres=0.3)
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img_path = ''.join([os.getcwd(), '/model/data/test0910.png'])
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point_path = ''.join([os.getcwd(), '/model/data/test0910.xyz'])
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self.img = cv2.imread(img_path)
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self.point = np.loadtxt(point_path).reshape((1080, 1440, 3))
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def get_position(self, Point_isVision=True):
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@ -46,16 +41,13 @@ class Detection:
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:param api: None
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:return: ret , img, (x,y,z), (nx, ny, nz)
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'''
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#ret, img, pm = self.camera_rvc.get_img_and_point_map() # 拍照,获取图像及
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ret = 1
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img = self.img
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pm = self.point
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ret, img, pm = self.camera_rvc.get_img_and_point_map() # 拍照,获取图像及
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if self.camera_rvc.caminit_isok == True:
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if ret == 1:
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if self.use_openvino_model == False:
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flag, det_cpu, dst_img, masks, category_names = self.model.model_inference(img, 0)
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else:
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flag, det_cpu, scores, masks, category_names = self.model.segment_objects(img)
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dst_img = img
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if flag == 1:
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xyz = []
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nx_ny_nz = []
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@ -76,10 +68,7 @@ class Detection:
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# 画box
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box_x1, box_y1, box_x2, box_y2 = item[0:4].astype(np.int32)
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if self.use_openvino_model == False:
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label = category_names[int(item[5])]
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else:
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label = class_names[int(item[4])]
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rand_color = (0, 255, 255)
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score = item[4]
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org = (int((box_x1 + box_x2) / 2), int((box_y1 + box_y2) / 2))
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@ -133,6 +122,10 @@ class Detection:
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select_point = np.array(select_point)
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pm_seg = select_point.reshape(-1, 3)
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pm_seg = pm_seg[~np.isnan(pm_seg).all(axis=-1), :] # 剔除 nan
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if pm_seg.size<300:
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print("分割点云数量较少,无法拟合平面")
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continue
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# cv2.imshow('result', piont_result)
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'''
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@ -186,7 +179,7 @@ class Detection:
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if _idx == None:
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return 1, img, None, None
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else:
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cv2.circle(img, (uv[_idx][0], uv[_idx][1]), 30, (0, 0, 255), 20) # 标出中心点
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cv2.circle(img, (uv[_idx][0], uv[_idx][1]), 30, (255, 0, 0), 20) # 标出中心点
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if Point_isVision==True:
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pcd = o3d.geometry.PointCloud()
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@ -208,7 +201,12 @@ class Detection:
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print("RVC X Camera capture failed!")
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return 0, None, None, None
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else:
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print("RVC X Camera is not opened!")
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return 0, None, None, None
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def release(self):
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self.camera_rvc.release()
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self.model.clear()
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@ -54,7 +54,6 @@ class Detection:
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flag, det_cpu, dst_img, masks, category_names = self.model.model_inference(img, 0)
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else:
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flag, det_cpu, scores, masks, category_names = self.model.segment_objects(img)
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dst_img = img
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if flag == 1:
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xyz = []
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nx_ny_nz = []
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@ -132,6 +131,9 @@ class Detection:
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select_point = np.array(select_point)
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pm_seg = select_point.reshape(-1, 3)
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pm_seg = pm_seg[~np.isnan(pm_seg).all(axis=-1), :] # 剔除 nan
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if pm_seg.size < 300:
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print("分割点云数量较少,无法拟合平面")
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continue
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# cv2.imshow('result', piont_result)
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'''
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