Instructions to use Emreuludasdemir/teknofest2026-task3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LightGlue
How to use Emreuludasdemir/teknofest2026-task3 with LightGlue:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| from __future__ import annotations | |
| from dataclasses import dataclass, field | |
| from typing import Any | |
| from src.core.frame_state import FrameEnvelope | |
| class SessionState: | |
| session_name: str | |
| video_name: str | |
| frames: list[FrameEnvelope] | |
| protocol_name: str = "official-repo-batch-v1" | |
| raw_frames: list[dict[str, Any]] = field(default_factory=list) | |
| raw_translations: list[dict[str, Any]] = field(default_factory=list) | |
| metadata: dict[str, Any] = field(default_factory=dict) | |
| class ReplaySummary: | |
| session_name: str | |
| frames_seen: int = 0 | |
| frames_submitted: int = 0 | |
| validation_failures: int = 0 | |
| submission_failures: int = 0 | |
| diagnostics: list[dict[str, Any]] = field(default_factory=list) | |