AI Product Shadows That
Actually Boost Sales

Why Shadows Matter for E-commerce

Product images on white backgrounds look flat. Shadows create depth, making products appear real and premium. Studies show:

• Products with realistic shadows have 18–30% higher click-through rates
• Shadow depth signals quality — used by Apple, Nike, and every major brand
• Consistent shadow style across catalog creates professional brand impression

Quickstart — curl

# Add soft studio shadow to your product
curl -X POST https://api.pixelapi.dev/v1/image/add-shadow \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://example.com/product.png",
    "shadow_type": "soft",
    "shadow_opacity": 0.5,
    "shadow_blur": 20,
    "shadow_offset_x": 8,
    "shadow_offset_y": 12
  }'

# Response:
# {"generation_id": "abc123", "status": "queued", "credits_used": 0.02}

# Poll for result:
curl https://api.pixelapi.dev/v1/generation/abc123 \
  -H "Authorization: Bearer YOUR_API_KEY"

Python — Full Example

import requests, time

API_KEY = "YOUR_API_KEY"
BASE = "https://api.pixelapi.dev"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

def add_shadow(image_url: str, shadow_type: str = "soft",
               opacity: float = 0.5, blur: int = 20) -> str:
    """Add shadow and return output URL."""
    
    # Queue the job
    r = requests.post(
        f"{BASE}/v1/image/add-shadow",
        headers=HEADERS,
        json={
            "image_url": image_url,
            "shadow_type": shadow_type,
            "shadow_opacity": opacity,
            "shadow_blur": blur,
            "shadow_offset_x": 8,
            "shadow_offset_y": 12,
        }
    )
    r.raise_for_status()
    gen_id = r.json()["generation_id"]
    
    # Wait for completion (typically 1-3 seconds)
    for _ in range(60):
        status = requests.get(
            f"{BASE}/v1/generation/{gen_id}", headers=HEADERS
        ).json()
        
        if status["status"] == "completed":
            return status["output_url"]
        elif status["status"] == "failed":
            raise Exception(f"Shadow generation failed: {status.get('error')}")
        time.sleep(1)
    
    raise TimeoutError("Shadow generation timed out")

# Example: full product photography pipeline
product_url = "https://example.com/sneaker_nobg.png"  # transparent PNG

# Try different shadow styles
for style in ["soft", "floating", "hard"]:
    result_url = add_shadow(product_url, shadow_type=style, opacity=0.45)
    print(f"  {style}: {result_url}")

# Cost: $0.010 per call = $0.030 for all 3 variants

Complete E-commerce Workflow (BG Removal + Shadow)

import requests, time
from pathlib import Path

API_KEY = "YOUR_API_KEY"
BASE = "https://api.pixelapi.dev"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

def product_photo_pipeline(image_path: str, shadow="soft") -> str:
    """
    Complete pipeline: raw product photo → professional e-commerce image
    Step 1: Remove background  ($0.005)
    Step 2: Add shadow         ($0.010)
    Total: $0.015 per product
    """
    # Step 1: Remove background
    with open(image_path, "rb") as f:
        r = requests.post(
            f"{BASE}/v1/image/remove-background",
            headers=HEADERS,
            files={"image": f},
            data={"output_format": "png"}
        )
    gen1 = r.json()["generation_id"]
    
    # Wait for BG removal
    while True:
        s = requests.get(f"{BASE}/v1/generation/{gen1}", headers=HEADERS).json()
        if s["status"] == "completed": break
        if s["status"] == "failed": raise Exception(f"BG removal failed")
        time.sleep(1)
    
    nobg_url = s["output_url"]
    
    # Step 2: Add shadow
    r2 = requests.post(
        f"{BASE}/v1/image/add-shadow",
        headers=HEADERS,
        json={"image_url": nobg_url, "shadow_type": shadow,
              "shadow_opacity": 0.45, "shadow_blur": 18}
    )
    gen2 = r2.json()["generation_id"]
    
    while True:
        s2 = requests.get(f"{BASE}/v1/generation/{gen2}", headers=HEADERS).json()
        if s2["status"] == "completed": break
        if s2["status"] == "failed": raise Exception(f"Shadow failed")
        time.sleep(1)
    
    return s2["output_url"]

# Process catalog
images = ["shoe1.jpg", "bag2.jpg", "watch3.jpg"]
for img in images:
    url = product_photo_pipeline(img)
    print(f"✅ {img} → {url}")
    # Total per image: $0.015

print(f"Total cost: ${len(images) * 0.015:.2f}")

Parameters Reference

{
  "image_url": "https://...",          // URL to PNG (transparent preferred)
  "shadow_type": "soft",               // soft | hard | natural | floating | none
  "shadow_opacity": 0.5,               // 0.0 (invisible) to 1.0 (full black)
  "shadow_blur": 20,                   // 0 (sharp) to 80 (very soft)  
  "shadow_offset_x": 8,                // -100 to 100 pixels (left/right)
  "shadow_offset_y": 12                // -100 to 100 pixels (up/down)
}