Free Image & Video Processing Toolkit#

7 free local AI tools + cloud AI generation (300+ models via Atlas Cloud API).

Local tools run 100% on your machine — no API keys, no cloud costs. Cloud generation tools provide access to state-of-the-art AI models for image and video creation.

Prerequisites#

• Python 3.10+ installed
• uv installed ( brew install uv / pip install uv / winget install astral-sh.uv)
• FFmpeg installed ( brew install ffmpeg / apt install ffmpeg / winget install ffmpeg)

Available Tools#

ToolScriptWhat It DoesImage Upscalescripts/upscale.py2x/4x super resolution using Real-ESRGANFace Enhancescripts/face-enhance.pyRestore and enhance faces using GFPGAN + CodeFormerBackground Removescripts/bg-remove.pyRemove image backgrounds, output transparent PNGObject Erasescripts/erase.pyErase unwanted objects using LaMa inpaintingFace Swapscripts/face-swap.pySwap faces between images using InsightFaceSmart Segmentscripts/segment.pySegment anything in images using FastSAMMedia Processscripts/media-process.pyConvert, compress, resize, extract with FFmpeg**AI Generate****scripts/ai-generate.py**Generate images/videos with 300+ cloud AI models

Usage#

All scripts use uv run for zero-setup execution — dependencies are automatically installed on first run.

Image Upscale (Real-ESRGAN)#

Upscale low-resolution images by 2x or 4x with AI super resolution.

bash

# 4x upscale (default)
uv run scripts/upscale.py input.jpg

# 2x upscale
uv run scripts/upscale.py input.jpg --scale 2

# Upscale with face enhancement
uv run scripts/upscale.py input.jpg --face-enhance

# Batch upscale a folder
uv run scripts/upscale.py ./photos/ --scale 4

# Custom output path
uv run scripts/upscale.py input.jpg -o upscaled.png

Face Enhance (GFPGAN + CodeFormer)#

Restore old photos, enhance blurry faces, fix low-quality portraits.

bash

# Enhance faces in an image (GFPGAN, default)
uv run scripts/face-enhance.py photo.jpg

# Use CodeFormer (better fidelity control)
uv run scripts/face-enhance.py photo.jpg --method codeformer

# Adjust fidelity (0=quality, 1=fidelity, default 0.5)
uv run scripts/face-enhance.py photo.jpg --method codeformer --fidelity 0.7

# Also upscale background (2x)
uv run scripts/face-enhance.py photo.jpg --bg-upscale 2

# Batch process
uv run scripts/face-enhance.py ./old-photos/

Background Remove (rembg)#

Remove backgrounds from images, output transparent PNG. Supports multiple AI models.

bash

# Remove background (default u2net model)
uv run scripts/bg-remove.py product.jpg

# Use specific model
uv run scripts/bg-remove.py photo.jpg --model isnet-general-use

# Batch process folder
uv run scripts/bg-remove.py ./products/ -o ./transparent/

# Keep only the foreground (alpha matting for fine edges)
uv run scripts/bg-remove.py portrait.jpg --alpha-matting

# Available models: u2net, u2netp, u2net_human_seg, u2net_cloth_seg,
#                   silueta, isnet-general-use, isnet-anime, sam

Object Erase (LaMa Inpainting)#

Remove unwanted objects from images using a mask.

bash

# Erase objects (white area in mask = erase)
uv run scripts/erase.py image.png --mask mask.png

# Auto-generate mask from coordinates (x,y,width,height)
uv run scripts/erase.py image.png --region 100,200,150,150

# Batch erase with matching masks (image1.png + image1_mask.png)
uv run scripts/erase.py ./images/ --mask-dir ./masks/

Face Swap (InsightFace)#

Swap faces between two images.

bash

# Swap face from source to target
uv run scripts/face-swap.py --source face.jpg --target photo.jpg

# Swap specific face index (when multiple faces detected)
uv run scripts/face-swap.py --source face.jpg --target group.jpg --face-index 0

# Custom output
uv run scripts/face-swap.py --source face.jpg --target photo.jpg -o result.png

Smart Segment (FastSAM)#

Segment any object in an image using text prompt, point, or bounding box.

bash

# Segment everything
uv run scripts/segment.py image.jpg

# Segment by text prompt
uv run scripts/segment.py image.jpg --text "the dog"

# Segment by point (x, y)
uv run scripts/segment.py image.jpg --point 400,300

# Segment by bounding box (x1,y1,x2,y2)
uv run scripts/segment.py image.jpg --box 100,100,400,400

# Output mask only
uv run scripts/segment.py image.jpg --text "car" --mask-only

Media Process (FFmpeg)#

Convert, compress, resize, extract frames, merge audio/video — powered by FFmpeg.

bash

# Convert format
uv run scripts/media-process.py convert input.mp4 output.webm

# Compress video (target size in MB)
uv run scripts/media-process.py compress input.mp4 --target-size 10

# Resize video
uv run scripts/media-process.py resize input.mp4 --width 1280 --height 720

# Extract frames as images
uv run scripts/media-process.py frames input.mp4 --fps 1 --output ./frames/

# Extract audio
uv run scripts/media-process.py audio input.mp4 -o audio.mp3

# Create GIF from video
uv run scripts/media-process.py gif input.mp4 --start 5 --duration 3 --fps 15

# Trim video
uv run scripts/media-process.py trim input.mp4 --start 00:01:00 --end 00:02:30

# Merge multiple videos
uv run scripts/media-process.py merge video1.mp4 video2.mp4 video3.mp4 -o combined.mp4

# Add watermark
uv run scripts/media-process.py watermark input.mp4 --image logo.png --position bottom-right

# Get media info
uv run scripts/media-process.py info input.mp4

AI Generate (Atlas Cloud API) — Gold Sponsor#

Generate images and videos using 300+ state-of-the-art AI models. Requires an Atlas Cloud API key.

IMPORTANT for AI agents: Before calling this script, you MUST first use Atlas Cloud MCP tools to find the correct model ID and its required parameters:

1. Call atlas_list_models to browse available models, or atlas_search_docs to search for a specific model
2. Call atlas_get_model_info with the model ID to get the exact parameter schema (different models use different parameters — some use size, others use aspect_ratio + resolution, etc.)
3. Then call the script with --model <full_model_id> and the correct parameters

bash

# Generate image (pass full model ID from Atlas Cloud)
uv run scripts/ai-generate.py image "A cat astronaut on the moon" --model black-forest-labs/flux-schnell --size 1024*1024

# Models using aspect_ratio + resolution (e.g. Nano Banana 2, Imagen4)
uv run scripts/ai-generate.py image "Anime girl with blue hair" --model google/nano-banana-2/text-to-image --aspect-ratio 1:1 --resolution 1k

# Models using size presets (e.g. Seedream)
uv run scripts/ai-generate.py image "Product photo on marble" --model bytedance/seedream-v5.0-lite --size 2048*2048

# Edit existing image
uv run scripts/ai-generate.py image "Make the sky sunset orange" --model bytedance/seedream-v5.0-lite/edit --image photo.jpg

# Generate video
uv run scripts/ai-generate.py video "Timelapse of cherry blossoms" --model alibaba/wan-2.6/text-to-video --size 1280*720

# Image-to-video
uv run scripts/ai-generate.py video "The person starts walking" --model alibaba/wan-2.6/image-to-video --image portrait.jpg

# Pass extra model-specific parameters as JSON
uv run scripts/ai-generate.py image "A logo" --model google/imagen4-ultra --extra '{"num_images": 4}'

# NSFW mode
uv run scripts/ai-generate.py image "Artistic figure study" --model black-forest-labs/flux-dev-lora --nsfw

Setup: Set ATLAS_CLOUD_API_KEY in environment variable or project .env file. Get your key at atlascloud.ai. Note: when using cloud generation, your prompts and image data will be sent to the Atlas Cloud API for processing.

Output#

All tools save output to ./output/ by default. Use -o or --output to specify a custom path.

Models#

Models are automatically downloaded on first use and cached locally:

ToolModelSizeCache LocationUpscaleRealESRGAN_x4plus64MB~/.cache/realesrgan/Face EnhanceGFPGANv1.4348MB~/.cache/gfpgan/Face EnhanceCodeFormer376MB~/.cache/codeformer/Background Removeu2net176MB~/.u2net/Object EraseLaMa200MB~/.cache/lama/Face Swapbuffalo_l + inswapper500MB~/.insightface/Smart SegmentFastSAM-s~23MBauto-downloaded by ultralytics

Total first-run download: ~1.5GB. All subsequent runs use cached models.

Tips#

• GPU Acceleration: All tools automatically use CUDA/MPS if available, falling back to CPU
• Batch Processing: Most tools accept a folder path for batch processing
• Memory: Face swap and segmentation may need 4GB+ RAM for large images
• First Run: First execution downloads AI models — subsequent runs are instant

Workflow Examples#

Combine local processing with cloud AI generation:

bash

# 1. Generate a product image with AI
uv run scripts/ai-generate.py image "Minimalist perfume bottle, studio lighting" --model bytedance/seedream-v5.0-lite --size 2048*2048

# 2. Upscale to 4x resolution
uv run scripts/upscale.py ./output/seedream-v5.0-lite_*.png --scale 4

# 3. Remove background for e-commerce
uv run scripts/bg-remove.py ./output/*_x4.png --alpha-matting

# 4. Generate a product video
uv run scripts/ai-generate.py video "A perfume bottle rotating slowly" --model kwaivgi/kling-v3.0-pro/text-to-video --duration 5

# 5. Add watermark to the video
uv run scripts/media-process.py watermark ./output/text-to-video_*.mp4 --image logo.png