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byted-tos-image-process AI Agent Skill

Quellcode ansehen: bytedance/agentkit-samples

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Installation

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

11

Installationen

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.

Installationen

Installationen 11
Globales Ranking #601 von 601

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So verwenden Sie diesen Skill

1

Install byted-tos-image-process by running npx skills add bytedance/agentkit-samples --skill byted-tos-image-process in your project directory. Führen Sie den obigen Installationsbefehl in Ihrem Projektverzeichnis aus. Die Skill-Datei wird von GitHub heruntergeladen und in Ihrem Projekt platziert.

2

Keine Konfiguration erforderlich. Ihr KI-Agent (Claude Code, Cursor, Windsurf usw.) erkennt installierte Skills automatisch und nutzt sie als Kontext bei der Code-Generierung.

3

Der Skill verbessert das Verständnis Ihres Agenten für byted-tos-image-process, und hilft ihm, etablierte Muster zu befolgen, häufige Fehler zu vermeiden und produktionsreifen Code zu erzeugen.

Was Sie erhalten

Skills sind Klartext-Anweisungsdateien — kein ausführbarer Code. Sie kodieren Expertenwissen über Frameworks, Sprachen oder Tools, das Ihr KI-Agent liest, um seine Ausgabe zu verbessern. Das bedeutet null Laufzeit-Overhead, keine Abhängigkeitskonflikte und volle Transparenz: Sie können jede Anweisung vor der Installation lesen und prüfen.

Kompatibilität

Dieser Skill funktioniert mit jedem KI-Coding-Agenten, der das skills.sh-Format unterstützt, einschließlich Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider und anderen Tools, die projektbezogene Kontextdateien lesen. Skills sind auf Transportebene framework-agnostisch — der Inhalt bestimmt, für welche Sprache oder welches Framework er gilt.

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

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