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byted-tos-image-process AI Agent Skill

View Source: bytedance/agentkit-samples

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Installation

npx skills add bytedance/agentkit-samples --skill byted-tos-image-process

11

Installs

Bytedance TOS Image Process Skill

This skill provides essential image processing functions for files stored in Bytedance's TOS (TeraObjectStore). It allows you to retrieve image metadata, convert formats, resize, and apply watermarks directly using the Volcengine TOS SDK.

Quick Start

1. Client Initialization

The following Python snippet demonstrates how to initialize the TosClientV2 from environment variables.

import os
import tos
from tos.exceptions import TosClientError, TosServerError

def create_client() -> tos.TosClientV2:
    """Initializes a TosClientV2 using AK/SK (and optional STS token) from environment variables."""
    try:
        ak = os.getenv('TOS_ACCESS_KEY')
        sk = os.getenv('TOS_SECRET_KEY')
        endpoint = os.getenv('TOS_ENDPOINT')
        region = os.getenv('TOS_REGION')
        security_token = os.getenv('TOS_SECURITY_TOKEN') # Optional, for STS

        if not all([ak, sk, endpoint, region]):
            raise ValueError("Required environment variables are missing (AK, SK, Endpoint, Region).")

        return tos.TosClientV2(
            ak=ak,
            sk=sk,
            endpoint=endpoint,
            region=region,
            security_token=security_token,
        )
    except (ValueError, ImportError) as e:
        print(f"Error initializing client: {e}")
        return None

# Create the client
client = create_client()

2. Basic Workflow

# (Assumes 'client' is initialized and 'bucket_name', 'object_key' are set)

# 1. Get Image Info
try:
    response = client.get_object(bucket_name, object_key, process="image/info")
    info_data = response.read()
    print("Image Info:", info_data.decode('utf-8'))
except TosServerError as e:
    print(f"Error getting image info: {e}")

# 2. Resize an Image and save locally
try:
    client.get_object_to_file(
        bucket_name,
        object_key,
        "resized_image.jpg",
        process="image/resize,w_500,m_lfit" # Resize to 500px width, lfit mode
    )
    print("Resized image saved to resized_image.jpg")
except TosServerError as e:
    print(f"Error resizing image: {e}")

# 3. Convert Image to WebP and save back to TOS
try:
    response = client.get_object(
        bucket_name,
        object_key,
        process="image/format,f_webp,q_80", # Convert to WebP, quality 80
        save_bucket="my-output-bucket",
        save_object="processed/image.webp"
    )
    save_result = response.read()
    print("Converted image saved to TOS:", save_result.decode('utf-8'))
except TosServerError as e:
    print(f"Error saving converted image to TOS: {e}")

Core Operations

All image processing is achieved by passing a process string to the get_object or get_object_to_file SDK methods.

1. Get Image Info (ImageInfo)

Retrieves metadata of an image file, such as format, dimensions, and EXIF data.

SDK Method: client.get_object(..., process="image/info")

response = client.get_object(bucket_name, object_key, process="image/info")
image_metadata = response.read().decode('utf-8')
print(image_metadata)

2. Convert Image Format (ImageFormat)

Converts an image to a different format (e.g., JPEG, PNG, WebP) and adjusts quality.

SDK Method: client.get_object_to_file(..., process="image/format,f_webp,q_80")

# Convert to PNG format
client.get_object_to_file(
    bucket_name,
    object_key,
    "output.png",
    process="image/format,f_png"
)

3. Resize Image (ImageResize)

Resizes an image based on specified width, height, and resizing mode.

SDK Method: client.get_object_to_file(..., process="image/resize,w_800,h_600,m_fill")

# Resize to a maximum width of 1024px, maintaining aspect ratio
client.get_object_to_file(
    bucket_name,
    object_key,
    "resized_1024.jpg",
    process="image/resize,w_1024"
)

4. Apply Watermark (ImageWatermark & ImageBlindWatermark)

Adds a visible or blind watermark to an image. Parameters are complex and should be constructed according to the official TOS documentation.

SDK Method: client.get_object_to_file(..., process="image/watermark,...")

# Example for a text watermark (parameters must be Base64-encoded)
# This is a conceptual example. Refer to official docs for exact keys.
import base64
text_b64 = base64.b64encode("My Watermark".encode()).decode()
process_rule = f"image/watermark,type_1,text_{text_b64},size_40,p_9"

client.get_object_to_file(
    bucket_name,
    object_key,
    "watermarked.jpg",
    process=process_rule
)

5. Generic Image Processing (ImageProcess)

A flexible entry point that accepts any valid image processing string.

SDK Method: client.get_object(..., process="<full-process-string>")

# Example: Apply a Gaussian blur (hypothetical parameters)
client.get_object_to_file(
    bucket_name,
    object_key,
    "blurred.jpg",
    process="image/blur,r_5,s_2"
)

Authorization

Authentication is handled by tos.TosClientV2. Provide credentials via environment variables.

Required Environment Variables

  • TOS_ACCESS_KEY
  • TOS_SECRET_KEY
  • TOS_ENDPOINT
  • TOS_REGION

Optional for STS

  • TOS_SECURITY_TOKEN

Best Practices

  • Error Handling: Wrap SDK calls in try...except blocks to handle TosClientError and TosServerError.
  • Parameter Construction: For complex operations like watermarking, carefully construct the process string according to the official TOS documentation. Base64-encode parameter values where required.
  • Client Reuse: Initialize the TosClientV2 once and reuse it for multiple operations.

Additional Resources

  • For detailed parameters of each operation, see REFERENCE.md.
  • For common end-to-end examples, see WORKFLOWS.md.
  • For executable Python examples, see the scripts/ directory.
  • For the definitive list of all processing parameters, always consult the official Volcengine TOS Image Processing documentation.

Installs

Installs 11
Global Rank #601 of 601

Security Audit

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How to use this skill

1

Install byted-tos-image-process by running npx skills add bytedance/agentkit-samples --skill byted-tos-image-process in your project directory. Run the install command above in your project directory. The skill file will be downloaded from GitHub and placed in your project.

2

No configuration needed. Your AI agent (Claude Code, Cursor, Windsurf, etc.) automatically detects installed skills and uses them as context when generating code.

3

The skill enhances your agent's understanding of byted-tos-image-process, helping it follow established patterns, avoid common mistakes, and produce production-ready output.

What you get

Skills are plain-text instruction files — not executable code. They encode expert knowledge about frameworks, languages, or tools that your AI agent reads to improve its output. This means zero runtime overhead, no dependency conflicts, and full transparency: you can read and review every instruction before installing.

Compatibility

This skill works with any AI coding agent that supports the skills.sh format, including Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider, and other tools that read project-level context files. Skills are framework-agnostic at the transport level — the content inside determines which language or framework it applies to.

Data sourced from the skills.sh registry and GitHub. Install counts and security audits are updated regularly.

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