Video Interlaced Upscaler

This is the "free" interlaced upscaler of the DJZ video family - the one with no upscale_model socket, no download, no GPU-heavy neural pass. If you're looking at VideoInterlaceGANV3 and wondering whether you actually need an ESRGAN file to get started, the answer is no. This V1 node does the whole job with pure PyTorch math: bilinear upscale, split into fields, blend, done.

The mechanism, in plain terms: it takes your images batch and upscales it to 1.5x the input_height / input_width you declare - the defaults are 720→1080 and 1280→1920, i.e. the classic 720p to 1080i conversion. Then it separates each frame into even and odd horizontal fields (that's the "interlaced" part - old broadcast video drew odd lines then even lines, which is why the artifact looks the way it does), applies motion compensation between fields controlled by blend_factor (0–0.5, default 0.25), and recombines. Higher blend_factor = smoother motion but softer field separation; lower = sharper, more visible interlacing. field_order (top_first vs bottom_first) picks which field leads, and matters if you're matching a specific source standard or you see odd motion artifacts.

Inputs you actually set: input_width and input_height should match your source's native resolution, not the resolution it happens to be at in the batch - the node uses these to compute the 1.5x target, so lying to it gives you the wrong output size. Everything else lives at its default and is fine.

Now the honest framing, because there are three interlaced upscalers in this pack and they're not interchangeable. V1 is the simplest and the most "effect-forward" - it's really simulating an interlaced broadcast look while bumping resolution, which is a legit aesthetic if you want that video-era texture. The GAN V3 does genuine AI detail restoration. And the community's speed favorite is Fast V4, which is what a well-known r/comfyui thread used to push 960x540 → 1920x1080 on an 8GB VRAM laptop in well under a minute - the interlaced family is genuinely one of the cheaper ways to get a watchable video upscale without a heavy model.

Where the three diverge is intent. If your goal is "more pixels that look like real 1080i," this V1 is a one-minute setup with zero model downloads. If your goal is "more detail" (the upscaling doc's second job - inventing detail that was never captured), you need the GAN version and a real upscaler model, because bilinear interpolation can't add content; it can only enlarge. Same family name, different job. Don't pick by which sounds cooler - pick by whether your source is clean-enough to just enlarge.

Install: ComfyUI Manager → "DJZ-Nodes", or cd ComfyUI/custom_nodes && git clone https://github.com/MushroomFleet/DJZ-Nodes && pip install -r requirements.txt. You're pulling the whole ~75-node pack for it, which is the DJZ catch - heavy requirements list, but no per-node model downloads. Output is an IMAGE batch at 1.5x resolution, ready for VideoCombine.