add old lci module
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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压缩相机客户端Python实现
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功能：连接服务器接收JPEG压缩视频流，解码并显示
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"""
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import socket
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import cv2
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import numpy as np
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import sys
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import time
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from PIL import Image
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import io
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def main():
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print("Starting Compressed Camera Client...")
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if len(sys.argv) != 3:
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print(f"Usage: {sys.argv[0]} <server_ip> <port>")
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return 1
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server_ip = sys.argv[1]
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port = int(sys.argv[2])
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print(f"Configuration: Server IP={server_ip}, Port={port}")
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# 创建TCP套接字
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print("Creating TCP socket...")
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sockfd = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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# 设置套接字超时
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sockfd.settimeout(5.0)
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print("TCP socket created successfully")
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try:
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# 连接到服务器
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print(f"Connecting to server {server_ip}:{port}...")
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sockfd.connect((server_ip, port))
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print(f"Connected to server: {server_ip}:{port}")
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# 关闭超时，改为非阻塞模式
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sockfd.setblocking(True)
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print("Socket set to blocking mode")
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# OpenCV窗口
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print("Creating OpenCV window...")
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# 尝试使用不同的窗口参数
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cv2.namedWindow("Compressed Camera Stream", cv2.WINDOW_GUI_NORMAL)
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# 设置固定的窗口大小
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cv2.resizeWindow("Compressed Camera Stream", 640, 480)
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# 确保窗口大小是固定的
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cv2.setWindowProperty("Compressed Camera Stream", cv2.WND_PROP_ASPECT_RATIO, cv2.WINDOW_KEEPRATIO)
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cv2.setWindowProperty("Compressed Camera Stream", cv2.WND_PROP_AUTOSIZE, cv2.WINDOW_AUTOSIZE)
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# 显示初始信息
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info_frame = np.zeros((480, 640, 3), dtype=np.uint8)
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cv2.putText(info_frame, "Connecting to server...", (50, 240),
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cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
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cv2.imshow("Compressed Camera Stream", info_frame)
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cv2.waitKey(100)
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frame_count = 0
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buffer = b'' # 用于累积数据的缓冲区
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total_bytes_received = 0
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jpeg_found_count = 0
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# 上次收到数据的时间
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last_receive_time = time.time()
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while True:
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try:
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# 接收数据
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data = sockfd.recv(8192)
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if not data:
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print("Server closed connection")
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return 0
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last_receive_time = time.time()
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total_bytes_received += len(data)
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print(f"Received {len(data)} bytes, total: {total_bytes_received} bytes")
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# 将新数据添加到缓冲区
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buffer += data
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# 仅保留最近的500KB数据，防止内存溢出
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if len(buffer) > 500 * 1024:
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print(f"Buffer size exceeded 500KB, trimming to 500KB")
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buffer = buffer[-500 * 1024:]
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# 检查缓冲区中是否有JPEG标记
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has_jpeg = b'\xff\xd8' in buffer
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print(f"Buffer contains JPEG SOI: {has_jpeg}, buffer size: {len(buffer)}")
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# JPEG文件格式标记
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JPEG_START = b'\xff\xd8' # SOI (Start of Image)
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JPEG_END = b'\xff\xd9' # EOI (End of Image)
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# 查找所有完整的JPEG帧
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while True:
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# 查找JPEG开始标记
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start_idx = buffer.find(JPEG_START)
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if start_idx == -1:
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# 没有找到开始标记
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print(f"No JPEG SOI found, buffer size: {len(buffer)}")
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# 清空大部分缓冲区，只保留末尾可能包含部分JPEG头的数据
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if len(buffer) > 1024:
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buffer = buffer[-1024:]
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print(f"Trimmed buffer to {len(buffer)} bytes")
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break
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# 查找当前开始标记后的结束标记
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end_idx = buffer.find(JPEG_END, start_idx + 2)
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if end_idx == -1:
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# 没有找到完整的结束标记
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print(f"Found JPEG SOI but no EOI, buffer size from SOI: {len(buffer) - start_idx}")
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# 保留从开始标记到缓冲区末尾的数据
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buffer = buffer[start_idx:]
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break
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# 提取完整的JPEG帧（包括结束标记）
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jpeg_frame = buffer[start_idx:end_idx + 2]
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jpeg_found_count += 1
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print(f"Extracted JPEG frame {jpeg_found_count}, size: {len(jpeg_frame)} bytes")
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# 从缓冲区中移除已处理的JPEG帧
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buffer = buffer[end_idx + 2:]
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print(f"Buffer remaining after extraction: {len(buffer)} bytes")
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# 只处理合理大小的JPEG帧（1KB到500KB）
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if 1024 <= len(jpeg_frame) <= 500 * 1024:
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try:
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# 使用PIL库来解码和显示图像
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image_stream = io.BytesIO(jpeg_frame)
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pil_image = Image.open(image_stream)
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if pil_image is not None:
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# 解码成功，显示帧
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frame_count += 1
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print(f"Frame {frame_count} decoded successfully, size: {pil_image.width}x{pil_image.height}")
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# 转换为OpenCV格式
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opencv_image = cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
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# 检查图像是否有重复的模式
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# 从截图来看，图像被分割成了3x3的网格
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# 这可能是因为图像高度是正常的3倍
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if opencv_image.shape[0] == 1440 and opencv_image.shape[1] == 640:
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# 高度是1440，是正常的3倍
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# 只显示图像的前480行
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fixed_image = opencv_image[:480, :, :]
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cv2.imshow("Compressed Camera Stream", fixed_image)
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print(f"Fixed frame by cropping to 640x480")
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elif opencv_image.shape[0] == 640 and opencv_image.shape[1] == 1920:
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# 宽度是1920，是正常的3倍
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# 只显示图像的前640列
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fixed_image = opencv_image[:, :640, :]
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cv2.imshow("Compressed Camera Stream", fixed_image)
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print(f"Fixed frame by cropping to 640x480")
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else:
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# 直接显示原始大小的图像
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cv2.imshow("Compressed Camera Stream", opencv_image)
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# 只在显示新帧后调用一次waitKey，确保图像刷新
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key = cv2.waitKey(1)
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if key == 27:
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print("ESC key pressed, exiting...")
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return 1
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else:
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print(f"Failed to decode JPEG frame {jpeg_found_count}")
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except Exception as e:
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print(f"Error decoding JPEG frame {jpeg_found_count}: {e}")
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# 尝试使用OpenCV的方式解码
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try:
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np_data = np.frombuffer(jpeg_frame, dtype=np.uint8)
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frame = cv2.imdecode(np_data, cv2.IMREAD_COLOR)
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if frame is not None:
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frame_count += 1
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print(f"Frame {frame_count} decoded with OpenCV, size: {frame.shape[1]}x{frame.shape[0]}")
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# 检查是否是3x3网格
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if frame.shape[0] > 480 and frame.shape[1] == 640:
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# 只显示前480行
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cv2.imshow("Compressed Camera Stream", frame[:480, :, :])
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else:
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cv2.imshow("Compressed Camera Stream", frame)
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key = cv2.waitKey(1)
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if key == 27:
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print("ESC key pressed, exiting...")
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return 1
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except Exception as e2:
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print(f"Failed with OpenCV too: {e2}")
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else:
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print(f"Invalid JPEG frame size: {len(jpeg_frame)} bytes, skipped")
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except socket.timeout:
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print("Socket timeout, no data received")
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except Exception as e:
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print(f"Error in receive loop: {e}")
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# 检查连接是否超时
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if time.time() - last_receive_time > 10:
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print("Connection timeout: No data received for 10 seconds")
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return 1
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# 检查是否按下ESC键退出
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key = cv2.waitKey(1)
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if key == 27:
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print("ESC key pressed, exiting...")
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break
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except socket.timeout as e:
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print(f"Connection timeout: {e}")
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return 1
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except Exception as e:
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print(f"Error: {e}")
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return 1
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finally:
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# 清理资源
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print("Cleaning up resources...")
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sockfd.close()
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cv2.destroyAllWindows()
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print(f"Client exiting. Total bytes received: {total_bytes_received}, JPEG frames found: {jpeg_found_count}, Successful frames: {frame_count}")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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