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FrankCV2048
2024-12-05 20:29:57 +08:00
parent 6f22ef051a dc640f461d
commit 65c4db96e0
14 changed files with 1228994 additions and 160 deletions
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16
Vision/camera_coordinate_dete.py
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@ -26,7 +26,7 @@ import os
class Detection:
def __init__(self, use_openvino_model=False, cameraType = 'RVC'): # cameraType = 'RVC' or cameraType = 'Pe'
def __init__(self, use_openvino_model=False, cameraType = 'Pe'): # cameraType = 'RVC' or cameraType = 'Pe'
"""
初始化相机及模型
:param use_openvino_model: 选择模型，默认使用openvino
@ -36,25 +36,25 @@ class Detection:
self.use_openvino_model = use_openvino_model
self.cameraType = cameraType
if self.use_openvino_model == False:
model_path = ''.join([os.getcwd(), '/Vision/model/pt/best.pt'])
model_path = ''.join([os.getcwd(), '/Vision/model/pt/one_bag.pt'])
device = 'cpu'
if self.cameraType == 'RVC':
self.camera_rvc = camera_rvc()
self.seg_distance_threshold = 0.01 # 1厘米
self.seg_distance_threshold = 10 # 1厘米
elif self.cameraType == 'Pe':
self.camera_rvc = camera_pe()
self.seg_distance_threshold = 20 # 2厘米
self.seg_distance_threshold = 10 # 2厘米
else:
print('相机参数错误')
return
self.model = yolov8_segment()
self.model.load_model(model_path, device)
else:
model_path = ''.join([os.getcwd(), '/Vision/model/openvino/best.xml'])
model_path = ''.join([os.getcwd(), '/Vision/model/openvino/one_bag.xml'])
device = 'CPU'
if self.cameraType == 'RVC':
self.camera_rvc = camera_rvc()
self.seg_distance_threshold = 0.01
self.seg_distance_threshold = 10
elif self.cameraType == 'Pe':
self.camera_rvc = camera_pe()
self.seg_distance_threshold = 20
@ -64,7 +64,7 @@ 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, Box_isPoint=True, First_Depth =True, Iter_Max_Pixel = 30, save_img_point=0, Height_reduce = 30, width_reduce = 30):
def get_position(self, Point_isVision=False, Box_isPoint=True, First_Depth =True, Iter_Max_Pixel = 30, save_img_point=0, Height_reduce = 50, width_reduce = 50):
"""
检测料袋相关信息
:param Point_isVision: 点云可视化
@ -75,7 +75,7 @@ class Detection:
:param Height_reduce: 检测框的高内缩像素
:param width_reduce: 检测框的宽内缩像素
:return ret: bool 相机是否正常工作
:return img: ndarry 返回img
:return img: ndarray 返回img
:return xyz: list 目标中心点云值形如[x,y,z]
:return nx_ny_nz: list 拟合平面法向量，形如[a,b,c]
:return box_list: list 内缩检测框四顶点，形如[[x1,y1],[],[],[]]

16
Vision/camera_coordinate_dete_img.py
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@ -30,23 +30,23 @@ class Detection:
self.use_openvino_model = use_openvino_model
self.cameraType = cameraType
if self.use_openvino_model == False:
model_path = ''.join([os.getcwd(), '/Vision/model/pt/best.pt'])
model_path = ''.join([os.getcwd(), '/Vision/model/pt/one_bag.pt'])
device = 'cpu'
self.model = yolov8_segment()
self.model.load_model(model_path, device)
else:
model_path = ''.join([os.getcwd(), '/Vision/model/openvino/best.xml'])
model_path = ''.join([os.getcwd(), '/Vision/model/openvino/one_bag.xml'])
device = 'CPU'
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=0.6, iou_thres=0.6)
img_path = ''.join([os.getcwd(), '/Vision/model/data/test0911.png'])
point_path = ''.join([os.getcwd(), '/Vision/model/data/test0911.xyz'])
img_path = ''.join([os.getcwd(), '/Vision/model/data/2024_11_29_10_05_58.png'])
point_path = ''.join([os.getcwd(), '/Vision/model/data/2024_11_29_10_05_58.xyz'])
self.img = cv2.imread(img_path)
self.point = np.loadtxt(point_path).reshape((1080, 1440, 3))
self.point = np.loadtxt(point_path).reshape((self.img.shape[0], self.img.shape[1], 3))
pass
def get_position(self, Point_isVision=False, Box_isPoint=False, First_Depth =True, Iter_Max_Pixel = 30, 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, First_Depth =True, Iter_Max_Pixel = 30, save_img_point=0, seg_distance_threshold = 10, Height_reduce = 50, width_reduce = 50):
"""
检测料袋相关信息
:param Point_isVision: 点云可视化
@ -167,7 +167,7 @@ class Detection:
'''
rect = cv2.minAreaRect(max_contour)
if rect[1][0] - width_reduce < 30 or rect[1][1] - Height_reduce < 30:
if rect[1][0] - width_reduce > 30 and rect[1][1] - Height_reduce > 30:
rect_reduce = (
(rect[0][0], rect[0][1]), (rect[1][0] - width_reduce, rect[1][1] - Height_reduce), rect[2])
else:

8
Vision/detect_person.py
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@ -1,5 +1,6 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
# @Time : 2024/9/25 11:47
# @Author : hjw
@ -23,7 +24,7 @@ class DetectionPerson:
:return: person [bool], img [ndarray]
"""
def __init__(self) -> None:
model_path = ''.join([os.getcwd(), '/Vision/model/pt/person.pt'])
model_path = ''.join([os.getcwd(), '/Vision/model/pt/person_detect.pt'])
ip = "192.168.1.65"
port = 554
name = "admin"
@ -48,6 +49,7 @@ class DetectionPerson:
if ret:
# img_src = cv2.imread(img_path)
img = self.precess_image(img_src, self.imgsz, self.half, self.cuda)
img = img[250:1000, 380:2000]
preds = self.model(img)
det = ops.non_max_suppression(preds, self.conf, self.iou, classes=None, agnostic=False, max_det=300,
nc=len(self.names))
@ -61,10 +63,10 @@ class DetectionPerson:
# cv2.imshow('img2', img_src)
# cv2.waitKey(1)
for result in results:
if self.names[result[5]]=="person":
if self.names[result[5]] == "person":
person = True
conf = round(result[4], 2)
#print(conf)
# print(conf)
self.draw_box(img_src, result[:4], conf, self.names[result[5]], lw, sf, tf)
return person, img_src

30
Vision/find_img_point.py Normal file
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@ -0,0 +1,30 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
# @Time : 2024/12/2 15:55
# @Author : hjw
# @File : find_img_point.py
'''
import cv2
import numpy as np
img = cv2.imread('./model/data/0925_01_28.png')
img2 = img[:600, 380:]
cv2.imshow('img2',img2)
cv2.imshow('img',img)
cv2.waitKey(0)
def on_EVENT_LBUTTONDOWN(event, x, y, flags, param):
if event == cv2.EVENT_LBUTTONDOWN:
xy = "%d,%d" % (x, y)
cv2.circle(img, (x, y), 1, (255, 0, 0), thickness = -1)
cv2.putText(img, xy, (x, y), cv2.FONT_HERSHEY_PLAIN,
1.0, (0,0,0), thickness = 1)
cv2.imshow("image", img)
cv2.namedWindow("image")
cv2.setMouseCallback("image", on_EVENT_LBUTTONDOWN)
while(1):
cv2.imshow("image", img)
if cv2.waitKey(0)&0xFF==27:
break
cv2.destroyAllWindows()

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1228800
Vision/model/data/2024_11_29_10_05_58.xyz Normal file
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5
Vision/model/openvino/metadata.yaml
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@ -1,6 +1,6 @@
description: Ultralytics YOLOv8n-seg model trained on D:\work\ultralytics-main\ultralytics\cfg\datasets\coco8-seg-dy.yaml
author: Ultralytics
date: '2024-09-10T13:48:59.901222'
date: '2024-12-02T17:16:53.470305'
version: 8.2.86
license: AGPL-3.0 License (https://ultralytics.com/license)
docs: https://docs.ultralytics.com
@ -11,4 +11,5 @@ imgsz:
- 640
- 640
names:
0: box
0: zheng
1: fan

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Vision/model/openvino/best.bin → Vision/model/openvino/one_bag.bin
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Vision/model/openvino/best.xml → Vision/model/openvino/one_bag.xml
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2
Vision/yolo/yolov8_pt_seg.py
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@ -330,7 +330,7 @@ class yolov8_segment():
preds = result[0]
proto = result[1][-1]
# NMS
det = non_max_suppression(preds, conf_thres=0.25, iou_thres=0.3, nc=len(self.model.CLASSES))[0]
det = non_max_suppression(preds, conf_thres=0.4, iou_thres=0.4, nc=len(self.model.CLASSES))[0]
if det.shape[0] != 0:
# bbox还原至原图尺寸
det[:, :4] = scale_boxes(img.shape[2:], det[:, :4], ori_img.shape)

7
get_position_test.py
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@ -22,10 +22,11 @@ import os
"""
测试 Vision
"""
def detectionPosition_test():
detection = Detection()
while True:
ret, img, xyz, nx_ny_nz, box = detection.get_position()
ret, img, xyz, nx_ny_nz, box = detection.get_position(Point_isVision=True)
if ret==1:
print('xyz点云坐标：', xyz)
print('nx_ny_nz法向量：', nx_ny_nz)
@ -37,7 +38,7 @@ def detectionPosition_test():
print("target_position:", target_position)
print("noraml_base", noraml_base)
cv2.imshow('img', img)
cv2.waitKey(1)
cv2.waitKey(0)
def take_photo_position_test():
detection = Detection()
@ -113,4 +114,4 @@ def bag_collection_test():
if __name__ == '__main__':
bag_collection_test()
detectionPosition_test()