Salesforce
/

FOFPred

@@ -1,198 +1,62 @@
 ---
 library_name: diffusers
 ---
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 ---
+license: apache-2.0
 library_name: diffusers
+pipeline_tag: image-to-image
+tags:
+  - optical-flow prediction
+  - motion prediction
+  - diffusion
 ---
+# FOFPred: Language-Driven Future Optical Flow Prediction
+**FOFPred** is a diffusion-based model that predicts future optical flow from a single image guided by natural language instructions. Given an input image and a text prompt describing a desired action (e.g., *"Moving the water bottle from right to left"*), FOFPred generates 4 sequential optical flow frames showing how objects would move.
+## Usage
+```python
+import torch
+from fofpred.pipelines.fofpred.pipeline_fofpred import FOFPredPipeline
+from fofpred.schedulers.scheduling_flow_match_euler_discrete import FlowMatchEulerDiscreteScheduler
+from PIL import Image
+pipeline = FOFPredPipeline.from_pretrained(
+    "salesforce/FOFPred",
+    torch_dtype=torch.bfloat16,
+).to("cuda")
+pipeline.scheduler = FlowMatchEulerDiscreteScheduler()
+results = pipeline(
+    prompt="Moving the water bottle from right to left.",
+    input_images=[Image.open("your_image.jpg")],
+    width=256,
+    height=256,
+    num_inference_steps=1,
+    num_images_per_prompt=4,
+    frame_count=4,
+    generator=torch.Generator(device="cuda").manual_seed(42),
+    output_type="pt",
+)
+flow_frames = results.images  # [B, F, C, H, W]
+```
+## Architecture
+| Component | Model |
+|-----------|-------|
+| **V-LLM** | Qwen2.5-VL-3B-Instruct |
+| **DiT** | OmniGen2Transformer3DModel |
+| **VAE** | FLUX.1-dev AutoencoderKL |
+| **Scheduler** | FlowMatchEulerDiscreteScheduler |
+## Acknowledgements
+- [OmniGen2](https://github.com/VectorSpaceLab/OmniGen2)
+- [Qwen2.5-VL](https://huggingface.co/Qwen/Qwen2.5-VL)
+- [Flux VAE](https://huggingface.co/black-forest-labs/FLUX.1-dev)
+## License
+Apache 2.0 — Copyright (c) 2025 Salesforce, Inc.