mirror of
https://github.com/NanjingForestryUniversity/supermachine--tomato-passion_fruit.git
synced 2025-11-08 22:34:00 +00:00
124 lines
4.2 KiB
Python
124 lines
4.2 KiB
Python
import win32file
|
|
import win32pipe
|
|
import io
|
|
from PIL import Image
|
|
import time
|
|
import logging
|
|
|
|
def send_data(pipe_send, long_axis, short_axis, defect_num, total_defect_area, rp):
|
|
|
|
|
|
start_time = time.time()
|
|
|
|
# width = rp.shape[0]
|
|
# height = rp.shape[1]
|
|
# print(width, height)
|
|
img_bytes = rp.tobytes()
|
|
# length = len(img_bytes) + 18
|
|
# print(length)
|
|
# length = length.to_bytes(4, byteorder='big')
|
|
# width = width.to_bytes(2, byteorder='big')
|
|
# height = height.to_bytes(2, byteorder='big')
|
|
long_axis = long_axis.to_bytes(2, byteorder='big')
|
|
short_axis = short_axis.to_bytes(2, byteorder='big')
|
|
defect_num = defect_num.to_bytes(2, byteorder='big')
|
|
total_defect_area = int(total_defect_area).to_bytes(4, byteorder='big')
|
|
# cmd_type = 'RIM'
|
|
# result = result.encode('ascii')
|
|
# send_message = b'\xaa' + length + (' ' + cmd_type).upper().encode('ascii') + long_axis + short_axis + defect_num + total_defect_area + width + height + img_bytes + b'\xff\xff\xbb'
|
|
send_message = long_axis + short_axis + defect_num + total_defect_area + img_bytes
|
|
# print(long_axis)
|
|
# print(short_axis)
|
|
# print(defect_num)
|
|
# print(total_defect_area)
|
|
# print(width)
|
|
# print(height)
|
|
|
|
try:
|
|
win32file.WriteFile(pipe_send, send_message)
|
|
print('发送成功')
|
|
# print(send_message)
|
|
except Exception as e:
|
|
logging.error(f'发送完成指令失败，错误类型：{e}')
|
|
return False
|
|
|
|
end_time = time.time()
|
|
print(f'发送时间：{end_time - start_time}秒')
|
|
|
|
return True
|
|
|
|
|
|
def receive_data(pipe, data_size):
|
|
try:
|
|
# 读取图片数据
|
|
result, img_data = win32file.ReadFile(pipe, data_size, None)
|
|
return img_data
|
|
except Exception as e:
|
|
print(f"Failed to receive data. Error: {e}")
|
|
return None
|
|
|
|
|
|
def create_pipes(pipe_receive_name, pipe_send_name):
|
|
# 打开或创建命名管道
|
|
pipe_receive = win32pipe.CreateNamedPipe(
|
|
pipe_receive_name,
|
|
win32pipe.PIPE_ACCESS_INBOUND,
|
|
win32pipe.PIPE_TYPE_BYTE | win32pipe.PIPE_WAIT,
|
|
1, 80000000, 80000000, 0, None
|
|
)
|
|
pipe_send = win32pipe.CreateNamedPipe(
|
|
pipe_send_name,
|
|
win32pipe.PIPE_ACCESS_OUTBOUND, # 修改为输出模式
|
|
win32pipe.PIPE_TYPE_BYTE | win32pipe.PIPE_WAIT,
|
|
1, 80000000, 80000000, 0, None
|
|
)
|
|
|
|
# 等待发送端连接
|
|
win32pipe.ConnectNamedPipe(pipe_receive, None)
|
|
# 等待发送端连接
|
|
win32pipe.ConnectNamedPipe(pipe_send, None)
|
|
print("Sender connected.")
|
|
print("receive connected.")
|
|
|
|
return pipe_receive, pipe_send
|
|
|
|
def process_images(pipe_receive, pipe_send):
|
|
image_count = 0
|
|
batch_size = 5
|
|
images = []
|
|
|
|
while True:
|
|
for i in range(5):
|
|
start_time = time.time() # 记录开始时间
|
|
img_data = receive_data(pipe_receive)
|
|
|
|
if img_data:
|
|
image = Image.open(io.BytesIO(img_data))
|
|
image = image.convert("L") # 示例处理：转换为灰度图
|
|
buf = io.BytesIO()
|
|
image.save(buf, format='JPEG')
|
|
buf.seek(0) # 重置buffer位置到开始
|
|
processed_data = buf.getvalue()
|
|
|
|
images.append(buf) # 存储 BytesIO 对象而不是 Image 对象
|
|
|
|
if len(images) >= batch_size:
|
|
# 发送最后一个处理后的图像
|
|
send_image_back_to_qt(pipe_send, images[-1].getvalue())
|
|
images = [] # 清空列表以开始新的批处理
|
|
time.sleep(0.01) # 添加适当的延迟,降低CPU使用率
|
|
print("Image received and saved.")
|
|
end_time = time.time() # 记录结束时间
|
|
duration_ms = (end_time - start_time) * 1000 # 转换为毫秒
|
|
print(f"Image {i + 1} received and displayed in {duration_ms:.2f} ms.") # 打印毫秒级的时间
|
|
image_count += 1 # 图片计数器增加
|
|
print(f"Image {image_count} received and displayed.")
|
|
|
|
def main():
|
|
pipe_receive_name = r'\\.\pipe\pipe_receive'
|
|
pipe_send_name = r'\\.\pipe\pipe_send'
|
|
pipe_receive, pipe_send = create_pipes(pipe_receive_name, pipe_send_name)
|
|
process_images(pipe_receive, pipe_send)
|
|
|
|
if __name__ == '__main__':
|
|
main() |