小米图像处理算法工程师-实习
实习兼职地点:武汉状态:招聘
任职要求
基础技能: 计算机、数学、电子信息等相关专业在校生,对计算机视觉领域有浓厚兴趣。 熟悉Python,能使用OpenCV、Pillow等工具进行图像处理,了解Pandas/NumPy等数据处理库。 了解机器学习基础概念(如监督学习、数据划分、评估指标等),有实际数据标注或清洗经验者优先。 加分项: 接触过主流标注工具(Labelme、CVAT等)或数据管理平台(如Label Studio)。 了解常见视觉任务(如分类、检测)的数据格式要求(COCO、VOC等)。 熟悉SQL或数据库操作,能处理大规模图像数据。 个人特质: 细致耐心,对数据质量敏感,具备较强的逻辑分析和问题排查能力。 良好的团队协作意识,愿意在算法与数据的交叉领域中深入学习。
工作职责
据构建与质量优化: 参与计算机视觉相关业务(如图像分类、目标检测、分割等)的数据采集、清洗、标注工作,为算法模型提供高质量的数据支持。 设计数据增强方案,挖掘数据潜在价值,提升数据集的多样性和鲁棒性。 数据处理流程开发: 协助搭建高效的数据处理流水线,优化数据存储、加载和预处理效率,支持算法团队的实验需求。 开发自动化工具或脚本,简化数据标注、校验和统计分析流程。 算法辅助支持: 配合算法工程师完成模型训练前的数据准备(如特征提取、样本平衡等),参与模型效果分析并提出数据层面的改进建议。 跟踪学术界/工业界的公开数据集和技术报告,为业务场景提供数据选型参考。 协作与文档: 与算法、产品团队紧密沟通,理解数据需求并输出清晰的数据说明文档。 维护数据版本和标注规范,确保数据可追溯性和一致性。
包括英文材料
OpenCV+
https://learnopencv.com/getting-started-with-opencv/
At LearnOpenCV we are on a mission to educate the global workforce in computer vision and AI.
https://opencv.org/university/free-opencv-course/
This free OpenCV course will teach you how to manipulate images and videos, and detect objects and faces, among other exciting topics in just about 3 hours.
Python+
https://liaoxuefeng.com/books/python/introduction/index.html
中文,免费,零起点,完整示例,基于最新的Python 3版本。
https://www.learnpython.org/
a free interactive Python tutorial for people who want to learn Python, fast.
https://www.youtube.com/watch?v=K5KVEU3aaeQ
Master Python from scratch 🚀 No fluff—just clear, practical coding skills to kickstart your journey!
https://www.youtube.com/watch?v=rfscVS0vtbw
This course will give you a full introduction into all of the core concepts in python.
图像处理+
https://opencv.org/blog/computer-vision-and-image-processing/
This fascinating journey involves two key fields: Computer Vision and Image Processing.
https://www.geeksforgeeks.org/python/image-processing-in-python/
Image processing involves analyzing and modifying digital images using computer algorithms.
https://www.youtube.com/watch?v=kSqxn6zGE0c
In this Introduction to Image Processing with Python, kaggle grandmaster Rob Mulla shows how to work with image data in python!
Pandas+
[英文] 10 minutes to pandas
https://pandas.pydata.org/docs/user_guide/10min.html
This is a short introduction to pandas, geared mainly for new users.
[英文] Cookbook - pandas
https://pandas.pydata.org/docs/user_guide/cookbook.html#cookbook
This is a repository for short and sweet examples and links for useful pandas recipes.
https://www.kaggle.com/learn/pandas
Solve short hands-on challenges to perfect your data manipulation skills.
https://www.youtube.com/watch?v=2uvysYbKdjM
I'm super excited for this one. We're doing another complete Python Pandas tutorial walkthrough.
https://www.youtube.com/watch?v=Mdq1WWSdUtw
Filtering, Joins, Indexing, Data Cleaning, Visualizations
NumPy+
https://numpy.org/doc/stable/user/absolute_beginners.html
NumPy (Numerical Python) is an open source Python library that’s widely used in science and engineering.
[英文] NumPy - Learn
https://numpy.org/learn/
Below is a curated collection of educational resources, both for self-learning and teaching others, developed by NumPy contributors and vetted by the community.
https://www.kaggle.com/code/themlphdstudent/learn-numpy-numpy-50-exercises-and-solution
This kernel uses exercises of NumPy from the Machine Learning Plus webpage
https://www.youtube.com/watch?v=KHoEbRH46Zk
If you've heard of Pandas and NumPy, you may think one is simply a superset of the other.
https://www.youtube.com/watch?v=QUT1VHiLmmI
Learn the basics of the NumPy library in this tutorial for beginners.
https://www.youtube.com/watch?v=VXU4LSAQDSc
This video serves as an introduction to the NumPy Python library.
机器学习+
https://www.youtube.com/watch?v=0oyDqO8PjIg
Learn about machine learning and AI with this comprehensive 11-hour course from @LunarTech_ai.
https://www.youtube.com/watch?v=i_LwzRVP7bg
Learn Machine Learning in a way that is accessible to absolute beginners.
https://www.youtube.com/watch?v=NWONeJKn6kc
Learn the theory and practical application of machine learning concepts in this comprehensive course for beginners.
https://www.youtube.com/watch?v=PcbuKRNtCUc
Learn about all the most important concepts and terms related to machine learning and AI.
SQL+
https://liaoxuefeng.com/books/sql/introduction/index.html
什么是SQL?简单地说,SQL就是访问和处理关系数据库的计算机标准语言。
https://sqlbolt.com/
Learn SQL with simple, interactive exercises.
https://www.youtube.com/watch?v=p3qvj9hO_Bo
In this video we will cover everything you need to know about SQL in only 60 minutes.
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
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实习
数据构建与质量优化: 参与计算机视觉相关业务(如图像分类、目标检测、分割等)的数据采集、清洗、标注工作,为算法模型提供高质量的数据支持。 设计数据增强方案,挖掘数据潜在价值,提升数据集的多样性和鲁棒性。 数据处理流程开发: 协助搭建高效的数据处理流水线,优化数据存储、加载和预处理效率,支持算法团队的实验需求。 开发自动化工具或脚本,简化数据标注、校验和统计分析流程。 算法辅助支持: 配合算法工程师完成模型训练前的数据准备(如特征提取、样本平衡等),参与模型效果分析并提出数据层面的改进建议。 跟踪学术界/工业界的公开数据集和技术报告,为业务场景提供数据选型参考。 协作与文档: 与算法、产品团队紧密沟通,理解数据需求并输出清晰的数据说明文档。 维护数据版本和标注规范,确保数据可追溯性和一致性。
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