Only with a mind free from distractions can one see the Way.
https://qwen.readthedocs.io/zh-cn/latest/framework/function_call.html
https://swift.readthedocs.io/zh-cn/latest/Customization/%E8%87%AA%E5%AE%9A%E4%B9%89%E6%95%B0%E6%8D%AE%E9%9B%86.html
https://github.com/Simple-Efficient/RL-Factory/blob/main/verl/tools/base_tool.py
https://github.com/QwenLM/Qwen-Agent/blob/main/qwen_agent/tools/web_extractor.py
图像擦除工具 https://github.com/Sanster/IOPaint
https://github.com/Anonym0u3/AttentiveEraser
ubuntu 文件搜索
grep -rnw . -e "CHALLENGING" --include="*.py"
Yunlong Lin Multimodal learning, Inverse Problems, AI Agents, Spatial Intelligence
https://github.com/XduSyL/EventGPT?tab=readme-ov-file [CVPR2025] EventGPT: Event Stream Understanding with Multimodal Large Language Models
https://event-fly.github.io/
@inproceedings{kong2025eventfly, title = {EventFly: Event Camera Perception from Ground to the Sky}, author = {Lingdong Kong and Dongyue Lu and Xiang Xu and Lai Xing Ng and Wei Tsang Ooi and Benoit R. Cottereau}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, year = {2025}, }
https://huggingface.co/datasets/drive-bench/arena/tree/main
https://github.com/OpenDriveLab/DriveLM/blob/main/docs/data_prep_nus.md
A curated list of resources dedicated to hyperbolic representation learning and its applications across various domains. Hyperbolic spaces are particularly suited for representing hierarchical data and tree-like structures, offering advantages over Euclidean embeddings for many complex data types.
"""
@author yutanglee
@description 这个代码可以免浏览器拨号上网，原理很简单，就是给认证服务器发送一个http请求。
@use 你需要提供上网账号、密码和运营商，是否采用手机端或者PC端是可选的。手机端和PC端是指，重邮的每个上网账号可以同时存在一个PC账号和手机端。
"""
from ast import arg
from pydoc import describe
import requests
import subprocess
import re
import argparse
import base64
def login(usr, psw, isp, ip, mobile=True):
url = 'http://192.168.200.2:801/eportal/?c=Portal&a=login&callback=dr1003&login_method=1&' +\
'user_account=%2C0%2C' + usr + '%40' + isp +'&user_password=' + psw + '&wlan_user_ip=' + ip + \
'&wlan_user_ipv6=&wlan_user_mac=000000000000&wlan_ac_ip=&wlan_ac_name=&jsVersion=3.3.3&v=10390'
if not mobile:
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36 Edg/114.0.1823.58'}
else:
headers = {
'User-Agent': 'Mozilla/5.0 (Linux; Android 6.0; Nexus 5 Build/MRA58N) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Mobile Safari/537.36 Edg/114.0.1823.58'}
r = requests.get(url=url, headers=headers)
return r.text
def get_local_ip():
try:
# 运行 ip a 命令获取网络接口信息
output = subprocess.check_output(["ip", "a"]).decode("utf-8")
# 使用正则表达式解析 IP 地址
ip_pattern = r"inet (\d+\.\d+\.\d+\.\d+)"
match = re.findall(ip_pattern, output)
# 筛选出以特定 IP 段开头的 IP 地址
target_ips = [ip for ip in match if ip.startswith("10.16.") or ip.startswith("10.20.")]
if target_ips:
return target_ips[0] # 返回第一个满足条件的 IP 地址
else:
return None
except subprocess.CalledProcessError:
return None
if __name__ == '__main__':
args = argparse.ArgumentParser()
args.add_argument('--user', type=str, default='<your_id>', help='your account for CQUPT network, maybe is your id number login ehall.cqupt.edu.cn')
args.add_argument('--psw', type=str, default='<your_password>', help='password')
args.add_argument('--isp', type=str, default='<your_isp>', help='cmcc|telecom|unicom|xyw')
args.add_argument('--mobile', action='store_true', help='do you want use mobile mode?')
args = args.parse_args()
if args.isp != 'cmcc' and args.isp != 'telecom' and args.isp != 'unicom' and args.isp != 'xyw':
print('运营商只支持cmcc|telecom|unicom|xyw 重新检查输入！')
exit(1)
ip = get_local_ip()
if ip is None:
ip = input("自动获取IP失败, 请你输入正确的IP: ")
print('your ip is:', ip)
print('your user is:', args.user)
print('your password is:', args.psw)
print('your isp is:', args.isp)
args.mobile = True
response = login(args.user, args.psw, args.isp, ip, args.mobile)
start_index = response.find('"result":"') + len('"result":"')
end_index = response.find('"', start_index)
result_value = response[start_index:end_index]
if result_value == '1':
print('登录成功！')
else:
start_index = response.find('"msg":"') + len('"msg":"')
end_index = response.find('"', start_index)
msg_encoded = response[start_index:end_index]
# 对msg进行Base64解码
msg_decoded = base64.b64decode(msg_encoded).decode('utf-8')
print(msg_decoded, response)
if msg_decoded == 'ldap auth error':
print('密码错误！')
elif msg_decoded == 'userid error1':
print('账号不存在！')
1、 题目： MSC-Bench: Benchmarking and Analyzing Multi-Sensor Corruption for Driving Perception
链接： https://t.zsxq.com/BRSA3
简介： MSC-Bench: 第一个针对多传感器自动驾驶感知模型在各种传感器损坏情况下的鲁棒性进行评估的综合基准
时间： 2025-01-10T23:52:48.526+0800
2、 题目： Hidden Biases of End-to-End Driving Datasets
链接：https://t.zsxq.com/BRSA3
A comprehensive collection of resources for hyperbolic space learning, representation, and deep learning implementations. 双曲空间学习、表示和深度学习实现的综合资源集合。
HyperbolicCV - Hyperbolic Computer Vision implementation
Hyperbolic Image Embeddings - Image embeddings in hyperbolic space
https://github.com/Charmve/OpenCC 道路极端场景综述
https://github.com/Thinklab-SJTU/Awesome-LLM4AD 综述地址
Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline. NeurIPS 22 Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving. CVPR 23 DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving. ICCV 23 Oral Think2drive: Efficient reinforcement learning by thinking in latent world model for quasi-realistic autonomous driving (in carla-v2). ECCV 24
This is a blog home page demo.
To use this layout, you should set both layout: BlogHome and home: true in the page front matter.
For related configuration docs, please see blog homepage.