Our review
Upscales rendered interior design images to 4K+ resolution using fal.ai's Clarity Upscaler with tunable resemblance and creativity parameters.
Strengths
- Automatically detects optimal scale factor to target 4K resolution
- High resemblance parameter preserves original details
- Simple integration with fal.ai API
- Saves upscaled images with clear naming convention
Limitations
- Requires a fal.ai API key and Python dependencies (fal_client, Pillow)
- Large output files (15-25 MB) may consume disk space
- The prompt is hardcoded for interior design; may not generalize well to other image types
When you need to upscale rendered interior design images to higher resolution while preserving details.
When you need real-time upscaling or when working with images that are not interior design renders.
Security analysis
CautionThe skill instructs Python scripts that upload files to an external API (fal.ai) and download results, which involves network and file system operations—legitimate but requires appropriate caution.
- •Uses network API calls and file I/O operations.
Examples
Upscale the most recent render to 4K.Upscale the image at projects/myproject/renders/living_room.png to 4K.Upscale the last rendered image by 2x.name: upscale description: Upscale rendered images to 4K+ resolution using fal.ai Clarity Upscaler. Use when the user wants to upscale, enhance resolution, make images sharper, or increase image size.
Upscale Images
Upscale rendered interior design images to 4K+ resolution using fal.ai's Clarity Upscaler — tunable resemblance/creativity for architectural photography.
Prerequisites
- fal.ai API key configured in
CLAUDE.local.md - Python with
fal_clientandPillowinstalled
Input
Accept via $ARGUMENTS or ask:
- Image path: path to the image to upscale (relative to project renders, or absolute)
- Scale factor: 2x or 4x (default: auto — pick scale so output is ~4K)
If the user says "upscale" without specifying an image, use the most recently created file in projects/${PROJECT_NAME}/renders/.
API Details
Provider: fal.ai
Model: fal-ai/clarity-upscaler
Capability: 1-4x upscale, adjustable resemblance (0-1) and creativity (0-1), prompt-guided
Workflow
Step 1: Resolve Image
import os, glob
# If no image specified, find most recent render
renders_dir = f"projects/{project_name}/renders"
files = sorted(glob.glob(os.path.join(renders_dir, "*.png")), key=os.path.getmtime, reverse=True)
# Exclude already-upscaled files
files = [f for f in files if "_4k_" not in os.path.basename(f) and "_upscaled_" not in os.path.basename(f)]
input_path = files[0]
Step 2: Auto-detect Scale
from PIL import Image
img = Image.open(input_path)
w, h = img.width, img.height
target = 3840 # 4K width
if w >= target:
scale = 2 # already large, 2x is enough
elif w * 4 <= target * 1.5:
scale = 4
else:
scale = 2
Step 3: Upload & Upscale
import fal_client
from datetime import datetime
# Read API key from CLAUDE.local.md
os.environ["FAL_KEY"] = "<fal_api_key_from_claude_local_md>"
image_url = fal_client.upload_file(input_path)
result = fal_client.subscribe("fal-ai/clarity-upscaler", arguments={
"image_url": image_url,
"scale": scale,
"resemblance": 0.9, # high = faithful to original
"creativity": 0.2, # low = minimal hallucination
"prompt": "photorealistic interior design, architectural photography, sharp details, high resolution",
})
# Download result
import urllib.request
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
basename = os.path.splitext(os.path.basename(input_path))[0]
out_path = os.path.join(renders_dir, f"{basename}_4k_{timestamp}.png")
urllib.request.urlretrieve(result["image"]["url"], out_path)
w = result["image"].get("width", "?")
h = result["image"].get("height", "?")
size_mb = os.path.getsize(out_path) / (1024 * 1024)
print(f"Upscaled: {w}x{h} ({size_mb:.1f} MB)")
print(f"Saved: {out_path}")
Step 4: Output
- Save upscaled image to same
renders/directory with_4k_suffix - Display the upscaled image to the user
- Report: original resolution → new resolution, file size
Output Naming Convention
{original_name}_4k_{timestamp}.png
Tuning Parameters
| Param | Default | Range | Effect |
|-------|---------|-------|--------|
| scale | auto | 1-4 | Upscale factor — auto-picks based on input size to target ~4K |
| resemblance | 0.9 | 0-1 | How faithful to original — 0.9 for interior design (preserve colors/layout) |
| creativity | 0.2 | 0-1 | How much AI "enhances" — keep low for architecture to avoid hallucination |
| prompt | (interior design) | text | Guides the upscaler — include relevant style keywords |
Gotchas
- Clarity Upscaler is the correct model —
fal-ai/clarity-upscaler. Controllable scale, resemblance, creativity. - Auto-scale logic — If input is already large (≥3840px wide), use scale=2. For ~1200px inputs, use scale=4. Prevents absurdly large outputs.
- Large output files — 4K PNGs can be 15-25 MB. Warn the user if disk space is a concern.
- Skip already-upscaled images — Filter out files with
_4k_or_upscaled_in the name. - API key — Read from
CLAUDE.local.md, fieldfal.ai. - Fallback — If Clarity fails, fall back to
fal-ai/aura-sr(fast GAN-based, fixed 4x, no params needed).
Session Relevant Skills
/render— generate images first, then upscale the best ones/compare-models— upscale the winning image after comparison/refine— if the upscaled image reveals quality issues not visible at low res, refine the prompt and re-render
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