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• Revision 30966 : eviter le moche ’doctype_ecrire’ lors de l’upgrade

  17 août 2009, par fil@… — Log

  eviter le moche ’doctype_ecrire’ lors de l’upgrade

• Decoding the h.264 stream from a COM port

  18 mars, par Peter

  I would like to know if there is a reliable way to decode an H.264 NAL stream coming through a serial port using software.

  


  So far, I have managed to decode a single frame using a python script. In this script, I first write the incoming data to a file, and when the end-of-frame marker 00_00_00_01 appears, I display the frame using ffplay.

  


  import serial
import subprocess
import os
import time

ser = serial.Serial('COM3', 115200, timeout=1)
output_file = "output.264"

# Variable to store the ffplay process
ffplay_process = None

# Open the file for writing in binary mode
with open(output_file, "wb") as file:

    print("Writing bytes to output.264. Waiting for the end-of-frame marker 0x00000001.")

    buffer = bytearray()
    marker = b'\x00\x00\x00\x01'

    try:
        while True:
            if ser.in_waiting:  # If there is data in the buffer
                data = ser.read(ser.in_waiting)  # Read all available bytes
                buffer.extend(data)

                # Check if the end-of-frame marker is in the buffer
                while marker in buffer:
                    index = buffer.index(marker) + len(marker)  # Position after the marker
                    frame = buffer[:index]  # Extract the frame
                    buffer = buffer[index:]  # Keep the remaining data

                    print(f"Frame recorded: {len(frame)} bytes")
                    file.write(frame)  # Write the frame to the file
                    file.flush()  # Force writing to disk

                    # Close the ffplay window if it is already open
                    if ffplay_process and ffplay_process.poll() is None:
                        ffplay_process.terminate()
                        ffplay_process.wait()  # Wait for the process to terminate

                    # Play the recorded frame, reopening the window
                    ffplay_process = subprocess.Popen(["ffplay", "-f", "h264", "-i", output_file])

    except KeyboardInterrupt:
        print("\nRecording stopped.")
    finally:
        # Close the serial port and the ffplay process
        ser.close()


  


  However, each time a new end-of-frame marker is detected, the ffplay window closes and reopens to show the next frame. It will flicker when transferring the video. Is there a way to display the frames in the same window for seamless playback when streaming video ?

  


  Or is there a better approach or software that is more suited for this task ? I do not know where to start, so I will be glad for any hints.

  


• Can't view and record graph at the same time using FFMpegWriter [closed]

  7 juillet 2024, par Barkın Özer

  So this code is used for graphing and logging sensor data coming from bluetooth ports. I wanted to add an function that will record the graph in mp4 format. In order to achieve this I used ffmpegWriter. The issue is while this code records the graph I can't view the graph at the same time.

  


  import serial
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation, FFMpegWriter
import openpyxl
from datetime import datetime

# Constants
GRAVITY = 9.81  # Standard gravity in m/s²

# Initialize serial connections to HC-06 devices
ser_x_accel = serial.Serial('COM4', 9600, timeout=1)  # X-axis acceleration data
ser_y_angle = serial.Serial('COM11', 9600, timeout=1)  # Y-axis angle data

# Initialize empty lists to store data
x_accel_data = []
y_angle_data = []
timestamps = []

# Initialize Excel workbook
wb = openpyxl.Workbook()
ws = wb.active
ws.title = "Sensor Data"
ws.append(["Timestamp", "X Acceleration (m/s²)", "Y Angle (degrees)"])

# Function to update the plot and log data
def update(frame):
    # Read data from serial connections
    line_x_accel = ser_x_accel.readline().decode('utf-8').strip()
    line_y_angle = ser_y_angle.readline().decode('utf-8').strip()
    
    try:
        # Parse and process X-axis acceleration data
        x_accel_g = float(line_x_accel)  # Acceleration in g read from serial
        x_accel_ms2 = x_accel_g * GRAVITY  # Convert from g to m/s²
        x_accel_data.append(x_accel_ms2)
        
        # Parse and process Y-axis angle data
        y_angle = float(line_y_angle)
        y_angle_data.append(y_angle)
        
        # Append timestamp
        timestamps.append(datetime.now())

        # Limit data points to show only the latest 100
        if len(x_accel_data) > 100:
            x_accel_data.pop(0)
            y_angle_data.pop(0)
            timestamps.pop(0)

        # Log data to Excel with timestamp
        timestamp_str = timestamps[-1].strftime("%H:%M:%S")
        ws.append([timestamp_str, x_accel_data[-1], y_angle_data[-1]])

        # Clear and update plots
        ax1.clear()
        ax1.plot(timestamps, x_accel_data, label='X Acceleration', color='b')
        ax1.legend(loc='upper left')
        ax1.set_ylim([-20, 20])  # Adjust based on expected acceleration range in m/s²
        ax1.set_title('Real-time X Acceleration Data')
        ax1.set_xlabel('Time')
        ax1.set_ylabel('Acceleration (m/s²)')
        ax1.grid(True)

        ax2.clear()
        ax2.plot(timestamps, y_angle_data, label='Y Angle', color='g')
        ax2.legend(loc='upper left')
        ax2.set_ylim([-180, 180])
        ax2.set_title('Real-time Y Angle Data')
        ax2.set_xlabel('Time')
        ax2.set_ylabel('Angle (degrees)')
        ax2.grid(True)

        # Update text boxes with latest values
        text_box.set_text(f'X Acceleration: {x_accel_data[-1]:.2f} m/s²')
        text_box2.set_text(f'Y Angle: {y_angle_data[-1]:.2f}°')
        
        # Save the workbook periodically (every 100 updates)
        if frame % 100 == 0:
            wb.save("sensor_data.xlsx")
        
    except ValueError:
        pass  # Ignore lines that are not properly formatted

# Setup the plots
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8))
text_box = ax1.text(0.05, 0.95, '', transform=ax1.transAxes, fontsize=12, verticalalignment='top', bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.5))
text_box2 = ax2.text(0.05, 0.95, '', transform=ax2.transAxes, fontsize=12, verticalalignment='top', bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.5))

# Animate the plots
ani = FuncAnimation(fig, update, interval=100)  # Update interval of 100ms

# Save the animation as a video file
writer = FFMpegWriter(fps=10, metadata=dict(artist='Me'), bitrate=1800)
ani.save("sensor_data.mp4", writer=writer)

plt.tight_layout()
plt.show()

# Save the workbook at the end of the session
wb.save("sensor_data.xlsx")



  


  I tried using OpenCV to record the graph but then I didn't even got any recording. I think solving this issue with my original code would be a better approach.