使用TensorFlow Object Detection API训练模型时遇'deployment'模块缺失错误

I’ve run into this exact issue before when setting up the TensorFlow Object Detection API in Colab—let’s break down why this happens and how to fix it quickly.

The Root Cause #

The deployment module isn’t inside the slim directory you added to your path—it lives directly in the models/research folder. Your current code only adds slim to sys.path, so Python can’t locate the deployment module that trainer.py is trying to import.

Step-by-Step Fix #

1. Add both required directories to your Python path
   Update your path setup code to include the main research directory along with slim:

   import sys
   # Add the main research directory
   sys.path.append('/content/models/research/')
   # Keep the slim directory addition
   sys.path.append('/content/models/research/slim/')
   

2. Verify Protobuf compilation (optional but recommended)
   If you haven’t already, make sure you’ve compiled the Protobuf files in the research directory—this ensures all API modules are properly set up:

   cd /content/models/research/
   !protoc object_detection/protos/*.proto --python_out=.
   

Why This Works #

By adding /content/models/research/ to sys.path, you’re telling Python to look in that directory for modules like deployment, which fixes the missing module error. The slim directory is still needed for other API dependencies, so we keep that line too.

内容的提问来源于stack exchange，提问作者Govinda Malavipathirana