Text-to-Image
Diffusers
Safetensors
English
medical
X-ray
Diffusion
Generation
Text-to-image
stable-diffusion
lora
fine_tune
Instructions to use Osama03/Medical-X-ray-image-generation-stable-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Osama03/Medical-X-ray-image-generation-stable-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Osama03/Medical-X-ray-image-generation-stable-diffusion") prompt = "Hey doc, I've been feeling really out of breath lately, especially when I'm walking up a flight of stairs or doing some light exercise. It's like my chest gets tight and I can't catch my breath. I've also been coughing up some stuff that's not quite right, it's been a few weeks now. And I've noticed a bit of weight loss, I'm not sure if that's related but it's been on my mind. I've been to a few doctors already, but they haven't been able to figure out what's going on. I'm hoping you can help." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
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README.md
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url: example.png
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Absolutely! Here's an updated and more detailed version of the `README.md`, expanding the model description and its potential applications:
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# Symptom-to-Medical-Image Generator
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| Application Area | Description |
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### Not for Use In:
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### Input Prompt:
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### Output:
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##
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* **Base Model**: `CompVis/stable-diffusion-v1-4`
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* **Fine-tuning Method**: LoRA (efficient, parameter-light adaptation)
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##
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This model is strictly intended for **research and educational** use. It is **not a substitute for professional medical judgment**. Use of synthetic medical images should follow all local regulatory and ethical guidelines.
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output:
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url: example.png
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# Symptom-to-Medical-Image Generator
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| Application Area | Description |
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| **Medical Research** | Generate datasets for hypothesis testing or model training without using real patient data. |
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| **Education & Training** | Teach students about correlations between symptoms and imaging in an interactive way. |
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| **AI-Aided Prototyping** | Test downstream diagnostic pipelines on synthetic but realistic image data. |
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| **Data Augmentation** | Enrich datasets for training classification/segmentation models. |
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| **Prompt-Based Exploration** | Investigate how changes in symptoms affect image generation (e.g., how “fever + cough” differs from “chest pain + shortness of breath”). |
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### Not for Use In:
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### Input Prompt:
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> "I've been feeling really out of breath lately, especially when I'm walking up a flight of stairs or doing some light exercise. It's like my chest gets tight and I can't catch my breath. "
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### Output:
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## Under the Hood
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* **Base Model**: `CompVis/stable-diffusion-v1-4`
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* **Fine-tuning Method**: LoRA (efficient, parameter-light adaptation)
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## Ethical & Legal Disclaimer
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This model is strictly intended for **research and educational** use. It is **not a substitute for professional medical judgment**. Use of synthetic medical images should follow all local regulatory and ethical guidelines.
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