在Amazon EC2运行猫狗图像识别Python脚本时如何处理输入输出文件？

Hey there! Let's walk through how to tackle your file handling and script execution on EC2 for that cat-dog image recognition model—no more guessing about inputs, outputs, or running scripts properly.

First, you need to get those 8000 images from S3 to your EC2 instance. The easiest way is using the AWS CLI:

• If your EC2 instance doesn't have AWS CLI installed yet:
  • For Amazon Linux: sudo yum install aws-cli -y
  • For Ubuntu: sudo apt-get update && sudo apt-get install aws-cli -y
• Pro tip (safer than manual credentials): Attach an IAM role to your EC2 instance with permissions to read from your S3 bucket. This way you don't have to enter access keys manually. Just create a role with AmazonS3ReadOnlyAccess (or restrict it to only your specific bucket) and assign it when launching your EC2 instance.
• Sync the images from S3 to a local folder on EC2:

  aws s3 sync s3://your-bucket-name/path/to/images/ ./ec2-image-dataset/
  

  This will copy all your images into a folder named ec2-image-dataset in your current EC2 directory.

Instead of pasting the script into the EC2 console, transfer your local script file directly to EC2:

• Use scp from your local Mac terminal to send the script:

  scp /path/to/your/local/cat_dog_script.py ec2-user@your-ec2-public-ip:/home/ec2-user/
  

  (Note: Replace ec2-user with ubuntu if you're using an Ubuntu EC2 instance, and use your actual EC2 public IP.)
• SSH into your EC2 instance, then install any required dependencies (like TensorFlow, Pillow, etc.):

  pip3 install tensorflow pillow numpy
  

• Finally, run the script like a normal file:

  python3 cat_dog_script.py
  

  Just make sure your script references the correct local image path (the ec2-image-dataset folder we created earlier—update the path in your script if it's hardcoded).

When your script finishes training, it will save the model file (like cat_dog_model.h5) to your EC2 instance's current directory. To make sure you don't lose it (EC2's default root storage is temporary if you terminate the instance):

• Copy the model back to S3 using AWS CLI:

  aws s3 cp ./cat_dog_model.h5 s3://your-bucket-name/path/to/save/model/
  

• Later, if you need to use the model again, you can pull it back from S3 to any EC2 instance (or your local Mac) with the same aws s3 cp command reversed.

Quick Extra Tips #

• Pick a GPU-enabled EC2 instance (like g4dn.xlarge)—training 8000 images on CPU will take forever, and GPU instances are worth the cost for this kind of work.
• Double-check that your script's image loading code points to the correct folder on EC2 (no more local Mac paths!).
• If you're running into permission issues with S3, verify your IAM role has the right access, or check that your bucket policy allows EC2 to interact with it.

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