akba08/ultra-realistic-cinematic-photography

Ultra Realistic Cinematic Photography Dataset

📘 Dataset Card: ultra-realistic-cinematic-photography

🏷️ Dataset Summary

ultra-realistic-cinematic-photography is a high-quality image dataset curated for training and fine-tuning generative models on ultra-realistic, cinematic-style photography. The dataset contains a diverse collection of images across multiple categories—wildlife, domestic animals, food, flowers, landscapes, nature scenes, and artistic compositions—all rendered in a consistent cinematic, photorealistic, shallow-depth-of-field visual style.

This dataset is ideal for:

• —High-fidelity image generation
• —Cinematic photography style transfer
• —Photorealistic diffusion model training
• —Aesthetic model conditioning
• —Benchmarking fine-tuned generative models

All images demonstrate a strong focus on:

• —Cinematic lighting
• —High dynamic range
• —Crisp details and textures
• —Shallow DOF / bokeh
• —Professional DSLR-like composition
• —Ultra-realistic rendering of subjects

🖼️ Dataset Contents

This dataset includes 165+ high-resolution images, spanning:

Wildlife & Animals

• —Lions, lionesses
• —White tigers
• —Snow leopards
• —Triceratops (fantasy realism)
• —Flamingos
• —Birds / seagulls
• —Cats & kittens
• —Dogs (indoor + beach scenes)

Nature & Landscapes

• —Mountain rivers
• —Coastal sunsets
• —Beach scenes
• —Flower fields
• —Tropical canyons

Food Photography

• —Gourmet dishes
• —Steaks, lamb chops
• —Pasta, soups, casseroles
• —Oven-baked dishes
• —Styled table settings All photographed in warm, cinematic, rustic lighting.

Floral Macro Photography

• —Lilies, daisies, blossoms
• —Dew-covered petals
• —Macro shallow-focus closeups

🧭 Intended Use

This dataset is designed for:

• —Training diffusion models, LDMs, GANs, or transformer-based vision models
• —Fine-tuning Stable Diffusion, SDXL, Flux, Sana, LlamaGen, and similar
• —Building cinematic aesthetic models
• —Conditioning models to generate:

• —Ultra-realistic animals
• —Photorealistic food
• —Cinematic landscapes
• —High-end macro floral photography

🔍 Keywords (Search Optimization)

photorealistic, realistic photography, cinematic photography, ultra-realistic images,
high-quality dataset, bokeh, shallow depth of field, wildlife photography, food photography,
flower photos, nature photography, cinematic lighting, HDR images, DSLR look, high-detail,
diffusion model dataset, generative AI dataset, realistic animals, macro flowers,
ultra-detailed photos, aesthetic dataset, image generation, huggingface dataset

📂 Dataset Structure

Format

• —JSONL annotations
• —Optimized for generative tasks

Image Resolutions

Common resolutions:

• —768×1024
• —1024×1024
• —1152×768
• —1408×704 (variations depending on aspect ratio)

Images are high quality and consistent in style.

🔧 How to Use

Load with Hugging Face Datasets

from datasets import load_dataset

dataset = load_dataset("your-username/ultra-realistic-cinematic-photography")

Example (Stable Diffusion Fine-tuning with Diffusers)

from diffusers import StableDiffusionPipeline
import torch

pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
pipe = pipe.to("cuda")

prompt = "a majestic lion resting on a rock at golden hour, ultra-realistic cinematic photography"
image = pipe(prompt).images[0]
image.show()

📜 Dataset Creation

Source and Curation

• —Images are curated and selected for consistent cinematic aesthetics.
• —Scenes were chosen to represent a broad range of natural textures, subjects, and lighting conditions.
• —The dataset focuses on ultra-realistic rendering with visually rich detail useful for generative modeling.

Ethical Considerations

• —No identifiable humans are present.
• —All content is safe for academic use.
• —Users should avoid generating harmful or misleading content.

📊 Statistics

📎 Citation

Coming Soon

📮 Contact / Issues

For questions, issues, improvements, or extended versions of the dataset, please open a GitHub issue or contact the dataset maintainer.