---
license: cc-by-nc-sa-4.0
pipeline_tag: image-to-image
library_name: libreyolo
tags:
- optical-flow
- dpflow
- libreflow
- libreyolo
---

# LibreDPFlowm-flow-spring

> **Non-commercial weights.** These DPFlow weights are licensed
> **CC BY-NC-SA 4.0** by their author (trained within ptlflow). They are for
> non-commercial use only and are **not** covered by LibreYOLO's MIT license.
> You are responsible for complying with the weight license.

DPFlow (CVPR 2025) optical flow, repackaged for LibreYOLO's `flow` task. This
checkpoint is the `spring` stage: fine-tuned on Spring from the Sintel stage (high-resolution benchmark).

DPFlow's dual-pyramid encoder picks its depth from the image diagonal (three
levels around 1K, one more per doubling), so it runs at the native resolution
of the frames and generalises to 4K and 8K inputs. LibreYOLO keeps that rule
and the upstream test schedule (4 refinement iterations per level).

## Usage

```python
from libreyolo import LibreYOLO

model = LibreYOLO("LibreDPFlowm-flow-spring.pt")  # auto-downloads from this repo
r = model(["frame_000.png", "frame_001.png"])[0]
r.flow.data      # (H, W, 2) float32, pixels, (dx, dy) from frame 0 to frame 1
r.flow.to_rgb()  # Middlebury colour wheel
```

## Source

Derived from [hmorimitsu/ptlflow](https://github.com/hmorimitsu/ptlflow)
(`ptlflow/models/dpflow`, code at commit `43cdc2b5fc7228e7090009a66e8e28e0b48e31ba`), weight file `dpflow-spring-69bac7fa.ckpt` from
the [weights1 release](https://github.com/hmorimitsu/ptlflow/releases/tag/weights1).
Copyright 2025 Henrique Morimitsu.

Morimitsu, H., Zhu, X., Cesar Jr, R. M., Ji, X., and Yin, X.-C. "DPFlow:
Adaptive Optical Flow Estimation with a Dual-Pyramid Framework." CVPR 2025.

## Modifications

State-dict metadata wrapping only. Learned parameters are unchanged.
See `weights/convert_dpflow_weights.py` in the
[LibreYOLO source repository](https://github.com/LibreYOLO/libreyolo).

## Parity

Checked on an RTX 3090 against ptlflow's own `DPFlow` (commit `43cdc2b5`) on 23 consecutive 640x360 frame pairs, fp32, TF32 off, deterministic cuDNN: max absolute difference 0.0 px, mean 0.0 px (bitwise identical).

## License

Weights: CC BY-NC-SA 4.0. See the [`LICENSE`](./LICENSE) and
[`NOTICE`](./NOTICE) files in this repository. The DPFlow code is Apache-2.0.