mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-26 19:06:11 +01:00
560dc68120
* Catch case where object does not have thumbnail data * Catch intel stats json decoding error * Catch division by zero
589 lines
17 KiB
Python
589 lines
17 KiB
Python
"""Utilities for services."""
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import asyncio
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import json
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import logging
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import os
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import re
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import signal
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import subprocess as sp
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import traceback
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from typing import Optional
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import cv2
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import psutil
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import py3nvml.py3nvml as nvml
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import requests
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from frigate.const import (
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DRIVER_AMD,
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DRIVER_ENV_VAR,
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FFMPEG_HWACCEL_NVIDIA,
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FFMPEG_HWACCEL_VAAPI,
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)
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from frigate.util.builtin import clean_camera_user_pass, escape_special_characters
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logger = logging.getLogger(__name__)
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def restart_frigate():
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proc = psutil.Process(1)
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# if this is running via s6, sigterm pid 1
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if proc.name() == "s6-svscan":
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proc.terminate()
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# otherwise, just try and exit frigate
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else:
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os.kill(os.getpid(), signal.SIGINT)
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def print_stack(sig, frame):
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traceback.print_stack(frame)
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def listen():
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signal.signal(signal.SIGUSR1, print_stack)
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def get_cgroups_version() -> str:
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"""Determine what version of cgroups is enabled."""
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cgroup_path = "/sys/fs/cgroup"
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if not os.path.ismount(cgroup_path):
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logger.debug(f"{cgroup_path} is not a mount point.")
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return "unknown"
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try:
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with open("/proc/mounts", "r") as f:
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mounts = f.readlines()
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for mount in mounts:
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mount_info = mount.split()
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if mount_info[1] == cgroup_path:
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fs_type = mount_info[2]
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if fs_type == "cgroup2fs" or fs_type == "cgroup2":
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return "cgroup2"
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elif fs_type == "tmpfs":
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return "cgroup"
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else:
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logger.debug(
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f"Could not determine cgroups version: unhandled filesystem {fs_type}"
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)
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break
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except Exception as e:
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logger.debug(f"Could not determine cgroups version: {e}")
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return "unknown"
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def get_docker_memlimit_bytes() -> int:
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"""Get mem limit in bytes set in docker if present. Returns -1 if no limit detected."""
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# check running a supported cgroups version
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if get_cgroups_version() == "cgroup2":
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memlimit_path = "/sys/fs/cgroup/memory.max"
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try:
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with open(memlimit_path, "r") as f:
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value = f.read().strip()
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if value.isnumeric():
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return int(value)
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elif value.lower() == "max":
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return -1
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except Exception as e:
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logger.debug(f"Unable to get docker memlimit: {e}")
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return -1
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def get_cpu_stats() -> dict[str, dict]:
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"""Get cpu usages for each process id"""
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usages = {}
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docker_memlimit = get_docker_memlimit_bytes() / 1024
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total_mem = os.sysconf("SC_PAGE_SIZE") * os.sysconf("SC_PHYS_PAGES") / 1024
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system_cpu = psutil.cpu_percent(
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interval=None
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) # no interval as we don't want to be blocking
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system_mem = psutil.virtual_memory()
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usages["frigate.full_system"] = {
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"cpu": str(system_cpu),
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"mem": str(system_mem.percent),
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}
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for process in psutil.process_iter(["pid", "name", "cpu_percent", "cmdline"]):
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pid = str(process.info["pid"])
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try:
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cpu_percent = process.info["cpu_percent"]
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cmdline = process.info["cmdline"]
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with open(f"/proc/{pid}/stat", "r") as f:
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stats = f.readline().split()
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utime = int(stats[13])
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stime = int(stats[14])
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start_time = int(stats[21])
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with open("/proc/uptime") as f:
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system_uptime_sec = int(float(f.read().split()[0]))
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clk_tck = os.sysconf(os.sysconf_names["SC_CLK_TCK"])
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process_utime_sec = utime // clk_tck
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process_stime_sec = stime // clk_tck
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process_start_time_sec = start_time // clk_tck
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process_elapsed_sec = system_uptime_sec - process_start_time_sec
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process_usage_sec = process_utime_sec + process_stime_sec
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cpu_average_usage = process_usage_sec * 100 // process_elapsed_sec
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with open(f"/proc/{pid}/statm", "r") as f:
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mem_stats = f.readline().split()
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mem_res = int(mem_stats[1]) * os.sysconf("SC_PAGE_SIZE") / 1024
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if docker_memlimit > 0:
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mem_pct = round((mem_res / docker_memlimit) * 100, 1)
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else:
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mem_pct = round((mem_res / total_mem) * 100, 1)
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usages[pid] = {
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"cpu": str(cpu_percent),
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"cpu_average": str(round(cpu_average_usage, 2)),
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"mem": f"{mem_pct}",
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"cmdline": clean_camera_user_pass(" ".join(cmdline)),
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}
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except Exception:
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continue
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return usages
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def get_physical_interfaces(interfaces) -> list:
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if not interfaces:
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return []
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with open("/proc/net/dev", "r") as file:
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lines = file.readlines()
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physical_interfaces = []
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for line in lines:
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if ":" in line:
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interface = line.split(":")[0].strip()
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for int in interfaces:
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if interface.startswith(int):
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physical_interfaces.append(interface)
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return physical_interfaces
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def get_bandwidth_stats(config) -> dict[str, dict]:
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"""Get bandwidth usages for each ffmpeg process id"""
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usages = {}
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top_command = ["nethogs", "-t", "-v0", "-c5", "-d1"] + get_physical_interfaces(
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config.telemetry.network_interfaces
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)
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p = sp.run(
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top_command,
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encoding="ascii",
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capture_output=True,
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)
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if p.returncode != 0:
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logger.error(f"Error getting network stats :: {p.stderr}")
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return usages
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else:
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lines = p.stdout.split("\n")
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for line in lines:
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stats = list(filter(lambda a: a != "", line.strip().split("\t")))
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try:
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if re.search(
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r"(^ffmpeg|\/go2rtc|frigate\.detector\.[a-z]+)/([0-9]+)/", stats[0]
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):
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process = stats[0].split("/")
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usages[process[len(process) - 2]] = {
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"bandwidth": round(float(stats[1]) + float(stats[2]), 1),
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}
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except (IndexError, ValueError):
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continue
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return usages
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def is_vaapi_amd_driver() -> bool:
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# Use the explicitly configured driver, if available
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driver = os.environ.get(DRIVER_ENV_VAR)
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if driver:
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return driver == DRIVER_AMD
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# Otherwise, ask vainfo what is has autodetected
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p = vainfo_hwaccel()
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if p.returncode != 0:
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logger.error(f"Unable to poll vainfo: {p.stderr}")
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return False
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else:
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output = p.stdout.decode("unicode_escape").split("\n")
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# VA Info will print out the friendly name of the driver
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return any("AMD Radeon Graphics" in line for line in output)
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def get_amd_gpu_stats() -> dict[str, str]:
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"""Get stats using radeontop."""
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radeontop_command = ["radeontop", "-d", "-", "-l", "1"]
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p = sp.run(
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radeontop_command,
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encoding="ascii",
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capture_output=True,
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)
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if p.returncode != 0:
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logger.error(f"Unable to poll radeon GPU stats: {p.stderr}")
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return None
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else:
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usages = p.stdout.split(",")
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results: dict[str, str] = {}
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for hw in usages:
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if "gpu" in hw:
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results["gpu"] = f"{hw.strip().split(' ')[1].replace('%', '')}%"
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elif "vram" in hw:
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results["mem"] = f"{hw.strip().split(' ')[1].replace('%', '')}%"
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return results
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def get_intel_gpu_stats() -> dict[str, str]:
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"""Get stats using intel_gpu_top."""
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intel_gpu_top_command = [
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"timeout",
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"0.5s",
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"intel_gpu_top",
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"-J",
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"-o",
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"-",
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"-s",
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"1",
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]
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p = sp.run(
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intel_gpu_top_command,
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encoding="ascii",
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capture_output=True,
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)
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# timeout has a non-zero returncode when timeout is reached
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if p.returncode != 124:
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logger.error(f"Unable to poll intel GPU stats: {p.stderr}")
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return None
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else:
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try:
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data = json.loads(f'[{"".join(p.stdout.split())}]')
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except json.JSONDecodeError:
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return {"gpu": "-%", "mem": "-%"}
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results: dict[str, str] = {}
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render = {"global": []}
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video = {"global": []}
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for block in data:
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global_engine = block.get("engines")
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if global_engine:
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render_frame = global_engine.get("Render/3D/0", {}).get("busy")
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video_frame = global_engine.get("Video/0", {}).get("busy")
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if render_frame is not None:
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render["global"].append(float(render_frame))
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if video_frame is not None:
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video["global"].append(float(video_frame))
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clients = block.get("clients", {})
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if clients and len(clients):
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for client_block in clients.values():
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key = client_block["pid"]
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if render.get(key) is None:
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render[key] = []
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video[key] = []
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client_engine = client_block.get("engine-classes", {})
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render_frame = client_engine.get("Render/3D", {}).get("busy")
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video_frame = client_engine.get("Video", {}).get("busy")
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if render_frame is not None:
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render[key].append(float(render_frame))
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if video_frame is not None:
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video[key].append(float(video_frame))
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if render["global"]:
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results["gpu"] = (
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f"{round(((sum(render['global']) / len(render['global'])) + (sum(video['global']) / len(video['global']))) / 2, 2)}%"
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)
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results["mem"] = "-%"
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if len(render.keys()) > 1:
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results["clients"] = {}
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for key in render.keys():
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if key == "global" or not render[key] or not video[key]:
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continue
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results["clients"][key] = (
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f"{round(((sum(render[key]) / len(render[key])) + (sum(video[key]) / len(video[key]))) / 2, 2)}%"
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)
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return results
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def try_get_info(f, h, default="N/A"):
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try:
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if h:
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v = f(h)
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else:
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v = f()
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except nvml.NVMLError_NotSupported:
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v = default
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return v
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def get_nvidia_gpu_stats() -> dict[int, dict]:
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results = {}
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try:
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nvml.nvmlInit()
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deviceCount = nvml.nvmlDeviceGetCount()
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for i in range(deviceCount):
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handle = nvml.nvmlDeviceGetHandleByIndex(i)
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meminfo = try_get_info(nvml.nvmlDeviceGetMemoryInfo, handle)
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util = try_get_info(nvml.nvmlDeviceGetUtilizationRates, handle)
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enc = try_get_info(nvml.nvmlDeviceGetEncoderUtilization, handle)
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dec = try_get_info(nvml.nvmlDeviceGetDecoderUtilization, handle)
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pstate = try_get_info(nvml.nvmlDeviceGetPowerState, handle, default=None)
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if util != "N/A":
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gpu_util = util.gpu
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else:
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gpu_util = 0
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if meminfo != "N/A":
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gpu_mem_util = meminfo.used / meminfo.total * 100
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else:
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gpu_mem_util = -1
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if enc != "N/A":
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enc_util = enc[0]
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else:
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enc_util = -1
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if dec != "N/A":
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dec_util = dec[0]
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else:
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dec_util = -1
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results[i] = {
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"name": nvml.nvmlDeviceGetName(handle),
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"gpu": gpu_util,
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"mem": gpu_mem_util,
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"enc": enc_util,
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"dec": dec_util,
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"pstate": pstate or "unknown",
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}
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except Exception:
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pass
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finally:
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return results
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def get_jetson_stats() -> dict[int, dict]:
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results = {}
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try:
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results["mem"] = "-" # no discrete gpu memory
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with open("/sys/devices/gpu.0/load", "r") as f:
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gpuload = float(f.readline()) / 10
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results["gpu"] = f"{gpuload}%"
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except Exception:
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return None
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return results
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def ffprobe_stream(ffmpeg, path: str) -> sp.CompletedProcess:
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"""Run ffprobe on stream."""
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clean_path = escape_special_characters(path)
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ffprobe_cmd = [
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ffmpeg.ffprobe_path,
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"-timeout",
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"1000000",
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"-print_format",
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"json",
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"-show_entries",
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"stream=codec_long_name,width,height,bit_rate,duration,display_aspect_ratio,avg_frame_rate",
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"-loglevel",
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"quiet",
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clean_path,
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]
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return sp.run(ffprobe_cmd, capture_output=True)
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def vainfo_hwaccel(device_name: Optional[str] = None) -> sp.CompletedProcess:
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"""Run vainfo."""
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ffprobe_cmd = (
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["vainfo"]
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if not device_name
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else ["vainfo", "--display", "drm", "--device", f"/dev/dri/{device_name}"]
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)
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return sp.run(ffprobe_cmd, capture_output=True)
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def get_nvidia_driver_info() -> dict[str, any]:
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"""Get general hardware info for nvidia GPU."""
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results = {}
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try:
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nvml.nvmlInit()
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deviceCount = nvml.nvmlDeviceGetCount()
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for i in range(deviceCount):
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handle = nvml.nvmlDeviceGetHandleByIndex(i)
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driver = try_get_info(nvml.nvmlSystemGetDriverVersion, None, default=None)
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cuda_compute = try_get_info(
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nvml.nvmlDeviceGetCudaComputeCapability, handle, default=None
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)
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vbios = try_get_info(nvml.nvmlDeviceGetVbiosVersion, handle, default=None)
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results[i] = {
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"name": nvml.nvmlDeviceGetName(handle),
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"driver": driver or "unknown",
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"cuda_compute": cuda_compute or "unknown",
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"vbios": vbios or "unknown",
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}
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except Exception:
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pass
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finally:
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return results
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def auto_detect_hwaccel() -> str:
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"""Detect hwaccel args by default."""
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try:
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cuda = False
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vaapi = False
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resp = requests.get("http://127.0.0.1:1984/api/ffmpeg/hardware", timeout=3)
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if resp.status_code == 200:
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data: dict[str, list[dict[str, str]]] = resp.json()
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for source in data.get("sources", []):
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if "cuda" in source.get("url", "") and source.get("name") == "OK":
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cuda = True
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if "vaapi" in source.get("url", "") and source.get("name") == "OK":
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vaapi = True
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except requests.RequestException:
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pass
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if cuda:
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logger.info("Automatically detected nvidia hwaccel for video decoding")
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return FFMPEG_HWACCEL_NVIDIA
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if vaapi:
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logger.info("Automatically detected vaapi hwaccel for video decoding")
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return FFMPEG_HWACCEL_VAAPI
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logger.warning(
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"Did not detect hwaccel, using a GPU for accelerated video decoding is highly recommended"
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)
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return ""
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async def get_video_properties(
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ffmpeg, url: str, get_duration: bool = False
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) -> dict[str, any]:
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async def calculate_duration(video: Optional[any]) -> float:
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duration = None
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if video is not None:
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# Get the frames per second (fps) of the video stream
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fps = video.get(cv2.CAP_PROP_FPS)
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total_frames = int(video.get(cv2.CAP_PROP_FRAME_COUNT))
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if fps and total_frames:
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duration = total_frames / fps
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# if cv2 failed need to use ffprobe
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if duration is None:
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p = await asyncio.create_subprocess_exec(
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ffmpeg.ffprobe_path,
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"-v",
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"error",
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"-show_entries",
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"format=duration",
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"-of",
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"default=noprint_wrappers=1:nokey=1",
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f"{url}",
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stdout=asyncio.subprocess.PIPE,
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stderr=asyncio.subprocess.PIPE,
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)
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await p.wait()
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if p.returncode == 0:
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result = (await p.stdout.read()).decode()
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else:
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result = None
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if result:
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try:
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duration = float(result.strip())
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except ValueError:
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duration = -1
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|
else:
|
|
duration = -1
|
|
|
|
return duration
|
|
|
|
width = height = 0
|
|
|
|
try:
|
|
# Open the video stream
|
|
video = cv2.VideoCapture(url)
|
|
|
|
# Check if the video stream was opened successfully
|
|
if not video.isOpened():
|
|
video = None
|
|
except Exception:
|
|
video = None
|
|
|
|
result = {}
|
|
|
|
if get_duration:
|
|
result["duration"] = await calculate_duration(video)
|
|
|
|
if video is not None:
|
|
# Get the width of frames in the video stream
|
|
width = video.get(cv2.CAP_PROP_FRAME_WIDTH)
|
|
|
|
# Get the height of frames in the video stream
|
|
height = video.get(cv2.CAP_PROP_FRAME_HEIGHT)
|
|
|
|
# Get the stream encoding
|
|
fourcc_int = int(video.get(cv2.CAP_PROP_FOURCC))
|
|
fourcc = (
|
|
chr((fourcc_int >> 0) & 255)
|
|
+ chr((fourcc_int >> 8) & 255)
|
|
+ chr((fourcc_int >> 16) & 255)
|
|
+ chr((fourcc_int >> 24) & 255)
|
|
)
|
|
|
|
# Release the video stream
|
|
video.release()
|
|
|
|
result["width"] = round(width)
|
|
result["height"] = round(height)
|
|
result["fourcc"] = fourcc
|
|
|
|
return result
|