cinematicShot-Pics-Flux Open Source Image Generation Model - Free Generation of Cinematic Image Scenarios

Cinematicshot Pics Flux

Developed by strangerzonehf

A text-to-image diffusion model based on LoRA technology, specializing in generating cinematic-style image scenes.

Image Generation Open Source License:Openrail #Cinematic Image Generation #LoRA Fine-tuned Diffusion Model #Portrait Scene Composition

Downloads 92

Release Time : 2/7/2025

Model Overview

This model fine-tunes the base diffusion model using LoRA technology, capable of generating cinematic images from text descriptions, with exceptional performance in detailed character scenes.

Model Features

Cinematic Image Generation

Specially optimized for generating images with a cinematic lens feel, including specific compositions, lighting, and scene setups.

LoRA Fine-tuning Technology

Uses LoRA technology for efficient fine-tuning of the base model, enhancing generation capabilities in specific domains while maintaining model lightweight.

Detail Control

Precisely controls elements such as clothing, poses, and backgrounds in generated images.

Model Capabilities

Text-to-Image Generation

Cinematic Scene Generation

Character Image Generation

Clothing Detail Control

Use Cases

Creative Design

Movie Concept Art Generation

Quickly generate concept art and scene previews for film or video projects.

Can generate scene images with specific styles and compositions.

Fashion Showcase

Display the effects of different clothing combinations in specific scenes.

Can precisely control clothing details and character poses.

Content Creation

Social Media Content

Create cinematic visual content for social media.

Quickly generates high-quality, stylistically consistent images.

🚀 CinematicShot-Pics-Flux

A LoRA model for generating cinematic shot images based on the black-forest-labs/FLUX.1-dev base model.

🚀 Quick Start

Installation

import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "strangerzonehf/cinematicShot-Pics-Flux"
trigger_word = "cinematic shot"  
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

Usage

You should use cinematic shot to trigger the image generation.

✨ Features

Generate high - quality cinematic shot images.
Based on the black - forest - labs/FLUX.1 - dev base model with LoRA fine - tuning.

📦 Installation

The installation steps are shown in the Quick Start section above.

💻 Usage Examples

Basic Usage

import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "strangerzonehf/cinematicShot-Pics-Flux"
trigger_word = "cinematic shot"  
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

# Generate an image
prompt = "cinematic shot, a beautiful landscape"
image = pipe(prompt).images[0]
image.save("generated_image.png")

📚 Documentation

Image Processing Parameters

Parameter	Value	Parameter	Value
LR Scheduler	constant	Noise Offset	0.03
Optimizer	AdamW	Multires Noise Discount	0.1
Network Dim	64	Multires Noise Iterations	10
Network Alpha	32	Repeat & Steps	17 & 2600
Epoch	22	Save Every N Epochs	1

Labeling

Labeling: florence2 - en(natural language & English)

Total Images Used for Training

Total Images Used for Training: 33

Best Dimensions & Inference

Dimensions	Aspect Ratio	Recommendation
1280 x 832	3:2	Best
1024 x 1024	1:1	Default

Inference Range

Recommended Inference Steps: 30–35

📄 License

This model is licensed under the creativeml - openrail - m license.

Download model

Weights for this model are available in Safetensors format. Download them in the Files & versions tab.

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