- In `image.py`, added a final batch bypass (`advance_check`) to disable face detection and cropping when the current batch completes the remaining video sequence. This prevents the generation of single-frame dummy batches at the end.
- In `video.py` and `loop.py`, updated `AutoLoopCalculator`, `AutoLoopCalculatorWan`, and `AutoLoopCalculatorLTX` to use an `absorption_threshold = equitable_target * 1.5`. This forces the calculator to absorb up to 50% extra remaining frames in a single batch, eliminating micro-cycles.
- Detected OS platform dynamically
- Added `ctypes.windll.kernel32.SetProcessWorkingSetSize` for deep RAM release on Windows
- Retained `malloc_trim` via `libc.so.6` for Linux environments
Inject `comfy.utils.ProgressBar` into the frame scanning loop in `VideoAnalyzerWithAudio`. This provides a visual native green progress bar directly on the node in the ComfyUI interface, giving real-time feedback during long video analyses without requiring the user to monitor the terminal output.
Update `IS_CHANGED` in `VideoAnalyzerWithAudio` to rely on the video path
and node parameters instead of `os.path.getmtime` and `time.time()`. This fixes
an issue where the node would constantly invalidate the cache and re-run on
every execution, rather than reusing cached results when inputs have not changed.
This commit patches the `SessionImageSender`, `AutoLoopCalculatorWan`,
and `AutoLoopCalculatorLTX` nodes to prevent infinite loops caused by
extreme truncation at the end of video sequences.
- `image.py`: Ensures `SessionImageSender` accepts the entire batch if no
faces are detected, rather than defaulting to frame 0, which previously
trapped the workflow in a 1-frame micro-cycle loop.
- `video.py`: Updates `AutoLoopCalculatorWan` to always round the final
chunk size up to the nearest multiple of 4, removing the strict
cropping logic that broke the 3D VAE rule.
- `loop.py`: Updates `AutoLoopCalculatorLTX` to always round the final
chunk size up to the nearest `8n + 1` value, removing the strict
cropping logic that broke the DiT rule.
- Enforced a strict memory cleanup sequence in `MeisoftVRAMDefragmenter` (including IPC cleanup and CUDA synchronization).
- Injected `PYTORCH_CUDA_ALLOC_CONF="max_split_size_mb:128"` in `__init__.py` to prevent VRAM micro-fragmentation.
- Added `unload_detector` option to `VideoAnalyzerWithAudio` to eagerly destroy the face detector model and free VRAM.
- Updated README.md with detailed explanations of the new features.
- Enforced a strict memory cleanup sequence in `MeisoftVRAMDefragmenter` (including IPC cleanup and CUDA synchronization).
- Injected `PYTORCH_CUDA_ALLOC_CONF="max_split_size_mb:128"` in `__init__.py` to prevent VRAM micro-fragmentation.
- Added `unload_detector` option to `VideoAnalyzerWithAudio` to eagerly destroy the face detector model and free VRAM.
- Created `MeisoftVRAMDefragmenter` in `vram_node.py` as a passthrough to force model unloading, Python garbage collection, and CUDA cache defragmentation.
- Registered the new node in `__init__.py`.
- Added light memory cleanup on intermediate batch loops in `loop.py`, alongside a heavy cleanup (including ctypes `malloc_trim`) at the end.
- Added `unload_detector_after_analysis` boolean flag to `VideoAnalyzerWithAudio` in `video.py` to allow releasing the BBOX detector model immediately after use.
- Implement `switch_node.py` with `MasterSwitch` handling native lazy evaluation.
- Register `MasterSwitch` in `__init__.py` using clean names.
- Intercept and apply Hot Graph Surgery in `loop.py` to strip out unneeded nodes in auto loop cycles for reduced VRAM usage.
Added `ConditionalAudioRouter` to `tools.py` with `torch` import to generate an empty audio tensor for bypassing a LipSync node during intermediate loops without breaking it. Registered node to `__init__.py`.
- Updated `SessionImageSender` to conditionally save keyframe only when not in the final cycle.
- Updated `IncrementalVideoStitcher` to return full concatenated tensor when in the final cycle, avoiding dummy frame output and blocking downstream nodes.
- Expose `IS_FINAL_CYCLE` boolean from `IncrementalVideoStitcher` to UI for downstream conditionals.
- Added Spanish documentation block to `README.md` explaining how to use the new `bbox_detector` port with Impact Pack.
- Added English documentation block to `README_EN.md` with the same instructions.
- Fixed tuple index extraction (`res[0]`) for `SEGS` object in bbox_detector.
- Silenced Ultralytics/YOLO console spam by wrapping detection logic in `redirect_stdout`.
- Upgraded the `while True:` loop to a `for` loop with `tqdm` for a clean progress bar, while preserving the RGB frame conversion logic for accuracy.
- Patches `AutoLoopCalculator` in `video.py` to add base proportional adjustment without VAE constraints.
- Patches `AutoLoopCalculatorLTX` in `loop.py` to enforce the strict 8n + 1 frame rule for LTX models, matching its calculation mathematically correctly for proportional chunking.
- Fixes `__pycache__` to be excluded correctly.
- Add optional `bbox_detector` input to `VideoAnalyzerWithAudio`.
- Implement GPU-accelerated face detection using external BBOX_DETECTOR models.
- Support both ImpactPack and standard ONNX bounding box output formats.
- Retain CPU-based OpenCV face detection as a fallback.
- Rename node in UI to "🕵️ Video Analyzer Face detector + Audio".
- Update README.md and README_EN.md to reflect new architecture and wiring.
- Renamed `ResTool32xLTX` to `ResTool64xLTX` and updated DIVISOR to 64 to prevent odd-dimension `ValueError`s when using latent downscale factors of 2.0 (IC-LoRA).
- Updated visual node name in `__init__.py` to accurately reflect the 64x divisor behavior to avoid technical debt.
- Updated documentation in `README.md` and `README_EN.md` to reflect the rename and explain the downscale compatibility logic.
- Implemented `AutoLoopCalculatorLTX` node to enforce `8n + 1` frame chunks.
- Added `ResTool32xLTX` node for strict 32x divisible resolutions with proper minimum pixel scaling.
- Updated `IncrementalVideoStitcher` (in `image.py`) to correctly subtract the overlapping anchor frame from global frame progression when LTX mode is active.
- Added `global_ltx_mode` reset in `SequentialLoopStart` to prevent state leakage to other non-LTX workflows.
- Registered nodes in `__init__.py` and updated `README.md` & `README_EN.md` with new features.
- Added AutoFPSLimiter class in `tools.py` to calculate `select_every_nth` and proportional `new_fps`.
- Registered `AutoFPSLimiter` in `__init__.py` under NODE_DISPLAY_NAME_MAPPINGS.
- Updated `README.md` and `README_EN.md` Architecture sections with details about the new node.
Changed the output type for the video path in the VideoAnalyzerWithAudio
node from STRING to `*` to allow for flexible wildcard connections in
ComfyUI. Also updated the return name to video_path to accurately
reflect the output variable.
- Moved port configuration from `SequentialLoopTrigger` to `SequentialLoopStart` to act as the single source of truth.
- Added a pre-flight check in `SequentialLoopStart` that pings the ComfyUI API endpoint `/system_stats` with a 2-second timeout.
- Aborts workflow execution immediately via `ValueError` if the port is incorrect or unreachable, saving hours of processing time by failing fast instead of at the end of the batch.
- Configured `SequentialLoopTrigger` to silently read `global_server_port` rather than requiring it as a node input.
- Ensured console debug logs remain cleanly formatted in Spanish to match user expectations.
- Añadida sección detallada sobre la nueva característica de Auto-Limpieza de VRAM en SequentialLoopTrigger.
- Añadidos detalles en Changelog (v1.5.3) en los README en español e inglés.
- Añadir las dependencias gc, torch y comfy.model_management en loop.py.
- Implementar vaciado profundo de VRAM al finalizar la generación de frames en el método trigger_next.
- Asegurar reinicio del contador global_accumulated_frames.
- Incluir soporte multiplataforma para el vaciado de cachés de PyTorch (CUDA, ROCm y MPS para Mac).
- Improve error handling in video.py to capture and display Torchaudio exceptions.
- Add explicit list of dependencies in requirements.txt.
- Introduce install.py for automated installation of Python and OS dependencies (FFmpeg).
- Complete redesign of Spanish and English READMEs with v1.5.2 Changelog, new features, and professional workflow setup.
Meisoft