Beginner score
55/100
Competition workspace
适合全日制普通高等教育在校学生，尤其是有目标检测、PaddlePaddle 模型推理和 Python 工程经验的人。线上可个人或团队参赛；若想进入线下分区选拔，还需通过学校代表队名额选拔。
Suggested next step
Decide whether this contest fits your current stage before you sink time into the leaderboard.
Beginner score
55/100
Learning value
58/100
Estimated effort
10-30 hours
Metric
Official scoring is described within th…
适合全日制普通高等教育在校学生，尤其是有目标检测、PaddlePaddle 模型推理和 Python 工程经验的人。线上可个人或团队参赛；若想进入线下分区选拔，还需通过学校代表队名额选拔。
Taken from the competition's official page.
Official QQ group for competition technical questions
Competition general contact email
If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.
PaddlePaddle 推理部署
目标检测
F1-score 与 IoU
Python 3.10
GPU 推理优化
JSON 结果生成
The real friction is usually not library usage. It is validation, time allocation, and task framing.
核心难点是在指定的 PaddlePaddle、Python 3.10 与 V100 GPU 环境中，把目标检测模型连同前后处理压到 20 FPS 以上；速度不达标会直接记为 0 分。同时还要按要求打包不超过限制的模型文件，并由固定名称的 predict.py 输出严格格式的 result.json。
This guide is the best pre-read if you want a cleaner start instead of trial-and-error.
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