AI-Based Image/Video Morphing System for Photo Studios

Project Overview

Technology Stack:
Python OpenCV TensorFlow / PyTorch GANs FFmpeg

Problem Statement:
Manual editing is time-consuming, costly, and maintaining consistent quality is challenging.

AI Component:
Generative AI models for morphing, style transfer, facial enhancement, and video frame interpolation.

Solution Summary:
AI-driven morphing, style transfer, and enhancement tools to automate editing for photo/video studios.

Impact:
Reduces studio editing time and costs, improves creativity, enhances global client satisfaction.

Sample Dataset: Image Metadata

ImageID ClientName Resolution FaceDetected LightingScore RequestedEffect
IMG_001 Rohan Sharma 1920x1080 Yes 78% Age Progression
IMG_002 Aarti Studio 1080x1080 Yes 84% Face Swap
IMG_003 Mona Photos 4096x2160 No 66% Color Enhancement
IMG_004 Classic Portraits 2560x1440 Yes 92% Beauty Retouch
IMG_005 Sunrise Studio 3840x2160 Yes 59% Caricature GAN

Sample Dataset: Morphing and Style Transfer Output

OutputID ImageID EffectApplied ProcessingTime (sec) GAN Model QualityScore
OUT_001 IMG_001 Age Progression (20 yrs) 14.2 StyleGAN3 95%
OUT_002 IMG_002 Face Swap 10.4 DeepSwap GAN 93%
OUT_003 IMG_003 HDR Color Boost 6.2 ColorGAN 89%
OUT_004 IMG_004 Beauty Retouch 8.9 FaceRetouch GAN 98%
OUT_005 IMG_005 Caricature 12.7 ToonGAN 92%

Sample Dataset: Video Morphing & Frame Interpolation

VideoID ClientName Duration FPS Before FPS After (Interpolated) EffectApplied
VID_001 Wedding Memories 2m 14s 24 60 Smooth Slow-Motion (RIFE Model)
VID_002 Ravi Studio 1m 30s 30 120 Frame Enhancement GAN
VID_003 FilmWorks 3m 12s 24 48 Color Style Transfer Video
VID_004 Elite Portraits 42s 30 60 Face Refinement Video
VID_005 Mystic Frames 1m 18s 25 90 Animation Style Transfer