用python写控制zed相机的代码
时间: 2023-03-29 18:01:17 浏览: 184
你可以使用ZED Python API来编写控制ZED相机的代码。首先,你需要安装ZED SDK并将其添加到Python路径中。然后,你可以使用以下代码来初始化相机并捕获图像:
```python
import pyzed.sl as sl
# 初始化ZED相机
zed = sl.Camera()
# 设置相机参数
init_params = sl.InitParameters()
init_params.camera_resolution = sl.RESOLUTION.HD720
init_params.camera_fps = 30
init_params.depth_mode = sl.DEPTH_MODE.PERFORMANCE
# 打开相机
err = zed.open(init_params)
if err != sl.ERROR_CODE.SUCCESS:
print("无法打开相机")
exit()
# 捕获图像
image = sl.Mat()
runtime_parameters = sl.RuntimeParameters()
zed.grab(runtime_parameters)
zed.retrieve_image(image, sl.VIEW.LEFT)
# 关闭相机
zed.close()
```
你可以根据需要修改相机参数和捕获图像的方式。
相关问题
zed2相机的python代码
以下是使用ZED 2相机的Python代码示例:
```python
import pyzed.sl as sl
def main():
# 初始化ZED相机
init_params = sl.InitParameters()
init_params.camera_resolution = sl.RESOLUTION.HD720
zed = sl.Camera()
err = zed.open(init_params)
if err != sl.ERROR_CODE.SUCCESS:
print("相机打开失败")
exit()
# 获取相机信息
camera_info = zed.get_camera_information()
print("相机型号:", camera_info.camera_model)
# 创建Mat对象以保存图像
image_left = sl.Mat()
image_right = sl.Mat()
# 创建RuntimeParameters对象以控制捕获
runtime_params = sl.RuntimeParameters()
# 开始捕获图像
while True:
if zed.grab(runtime_params) == sl.ERROR_CODE.SUCCESS:
# 获取左右图像
zed.retrieve_image(image_left, sl.VIEW.LEFT)
zed.retrieve_image(image_right, sl.VIEW.RIGHT)
# 在这里可以对图像进行处理
if __name__ == "__main__":
main()
```
需要注意的是,这是一个简单的示例代码,可能需要根据具体应用场景进行修改。另外,需要安装ZED Python API才能运行该代码。
写出用zed相机调用yolo v7模型的代码
以下是可以用zed相机调用yolo v7模型的Python代码示例:
首先,您需要安装zed相机SDK和yolo v7模型,并安装OpenCV和其他必要的库。然后,您可以使用以下代码:
```python
import cv2
import pyzed.sl as sl
import numpy as np
# Load the YOLOv7 object detection model
model = cv2.dnn.readNetFromDarknet("yolov7.cfg", "yolov7.weights")
# Set the input size
input_size = (416, 416)
# Set the confidence threshold
confidence_threshold = 0.5
# Open the ZED camera
zed = sl.Camera()
init = sl.InitParameters()
init.camera_resolution = sl.RESOLUTION.HD720
init.depth_mode = sl.DEPTH_MODE.NONE
init.camera_fps = 30
err = zed.open(init)
if err != sl.ERROR_CODE.SUCCESS:
print(repr(err))
zed.close()
exit()
# Capture frames from the ZED camera and resize them
while True:
# Grab a new image from the ZED camera
runtime_parameters = sl.RuntimeParameters()
left_image = sl.Mat()
zed.grab(runtime_parameters)
zed.retrieve_image(left_image, sl.VIEW.LEFT)
# Convert the image to a format that can be processed by YOLOv7
image = cv2.resize(left_image.get_data(), input_size)
blob = cv2.dnn.blobFromImage(image, 1/255.0, input_size, swapRB=True, crop=False)
# Set the inputs and run the YOLOv7 model
model.setInput(blob)
outputs = model.forward()
# Filter the outputs by confidence threshold and draw bounding boxes
for o in outputs:
for detection in o:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
if confidence > confidence_threshold:
x, y, w, h = detection[:4] * np.array([left_image.get_width(), left_image.get_height()] * 2)
xmin, ymin, xmax, ymax = int(x - w/2), int(y - h/2), int(x + w/2), int(y + h/2)
cv2.rectangle(left_image.get_data(), (xmin, ymin), (xmax, ymax), (255,0,0), 2)
# Display the processed image
cv2.imshow("YOLOv7 object detection", left_image.get_data())
# Exit loop on ESCAPE
key = cv2.waitKey(1)
if key == 27:
break
# Release the ZED camera
zed.close()
# Close the OpenCV window
cv2.destroyAllWindows()
```
请注意,以上代码可能需要根据您的要求进行修改。