PixelAPI - AI Image Processing API | Background Removal, Upscaling, Generation

Official Python SDK for PixelAPI — 2x cheaper than alternatives. Powered by bare-metal GPUs.

Why PixelAPI?

• 50% cheaper than Remove.bg, Cloudinary AI, Replicate
• Bare-metal GPUs — no cold starts, consistent speed
• One API for background removal, upscaling, generation, object removal, face restoration
• No usage limits — process 10,000+ images/day with no throttling
• Simple pricing — $0.001–$0.05 per operation, no monthly fees

Alternatives to Remove.bg & Cloudinary

Service	Background Removal	4x Upscale	Image Generation
PixelAPI	$0.005	$0.005	$0.001
Remove.bg	$0.09	N/A	N/A
Cloudinary AI	$0.10	$0.15	N/A
Replicate	$0.012	$0.012	$0.003

Installation

pip install pixelapi

Quick Start

from pixelapi import PixelAPI

client = PixelAPI("your_api_key")

# Remove background
result = client.remove_background("product.jpg")
result.save("output.png")

# Generate image
result = client.generate("A sunset over mountains", model="flux-schnell")
result.save("generated.png")

# Upscale 4x
result = client.upscale("photo.jpg", scale=4)
result.save("upscaled.png")

Features

Background Removal

# Remove background → transparent PNG
result = client.remove_background("product.jpg")

# Replace with new background
result = client.replace_background(
    image="person.jpg",
    background="beach.jpg"
)

# Or generate background from text
result = client.replace_background(
    image="person.jpg",
    prompt="professional office background"
)

Image Generation

result = client.generate(
    prompt="minimalist product photo of a watch",
    model="flux-schnell",  # or "sdxl"
    width=1024,
    height=1024,
    negative_prompt="blurry, low quality"
)
result.save("generated.png")

Image Enhancement

# 4x upscaling
result = client.upscale("photo.jpg", scale=4)

# Face restoration
result = client.restore_face("old_photo.jpg")

Object Manipulation

# Remove unwanted objects
result = client.remove_object(
    image="photo.jpg",
    mask="mask.png"  # white = remove
)

# Remove text/watermarks
result = client.remove_text("watermarked.jpg")

Advanced Features

# Add realistic shadow
result = client.add_shadow(
    image="product.png",
    shadow_opacity=0.5,
    shadow_blur=20
)

# Extend image borders (outpainting)
result = client.outpaint(
    image="photo.jpg",
    direction="all",
    pixels=256,
    prompt="continue the landscape"
)

Batch Processing

# Process multiple images efficiently
batch = client.batch(
    operation="remove-bg",
    images=["photo1.jpg", "photo2.jpg", "photo3.jpg"]
)

# Wait for completion
results = batch.wait()
for i, result in enumerate(results):
    result.save(f"output_{i}.png")

Account Management

# Check usage and credits
usage = client.get_usage()
print(f"Credits remaining: {usage['credits_remaining']}")
print(f"Credits used this month: {usage['credits_used']}")

# List available models
models = client.get_models()
print(models)

Examples

See the examples/ directory for complete working examples:

• remove_background.py - Basic background removal
• generate_images.py - Text-to-image generation
• batch_processing.py - Process multiple images
• product_photo.py - E-commerce product photography workflow

API Reference

Methods

• remove_background(image) - Remove image background
• replace_background(image, background=None, prompt=None) - Replace background
• generate(prompt, model, width, height, ...) - Generate image from text
• upscale(image, scale) - Upscale image 2x or 4x
• restore_face(image) - Restore and enhance faces
• remove_object(image, mask) - Remove objects using mask
• remove_text(image) - Remove text/watermarks
• add_shadow(image, shadow_opacity, ...) - Add realistic shadow
• outpaint(image, direction, pixels, prompt) - Extend image borders
• batch(operation, images, **kwargs) - Batch processing
• get_usage() - Get credit usage
• get_models() - List available models

Image Input

All methods accept images as:

• File path: "photo.jpg"
• URL: "https://example.com/image.jpg"
• Bytes: open("photo.jpg", "rb").read()
• Base64 string

Error Handling

from pixelapi import PixelAPI, PixelAPIError, AuthenticationError, RateLimitError

try:
    result = client.remove_background("photo.jpg")
except AuthenticationError:
    print("Invalid API key")
except RateLimitError:
    print("Rate limit exceeded")
except PixelAPIError as e:
    print(f"API error: {e.message}")

Pricing

Operation	Cost	Remove.bg	Cloudinary
Background removal	$0.005	$0.09	$0.10
Image generation	$0.001	N/A	N/A
4x upscale	$0.005	N/A	$0.15
Face restoration	$0.005	N/A	$0.12
Object removal	$0.020	N/A	$0.10

No monthly fees. No usage limits. Pay only for what you use.

Get API Key

1. Visit https://pixelapi.dev/app/
2. Sign up (free tier includes 100 credits)
3. Copy your API key from dashboard

Links

• 🌐 Website
• 📚 Documentation
• 🔑 Get API Key
• 💬 Discord Community

License

MIT

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Keywords: background removal, image upscaling, AI image generation, object removal, face restoration, image processing API, remove.bg alternative, cloudinary alternative, replicate alternative, AI image API