fixed resolution bug

README.md

@@ -46,16 +46,17 @@ LoadImage ──► IMAGE ──┘            ▲
 ```
 
 - **`image`** — the conditioning image (the grayscale / lineart page for
-  colorization). It is resized to `target_megapixels` (aspect-preserving,
+  colorization). It is resized to at most `target_megapixels` (aspect-preserving,
   VAE/patch-snapped) and VAE-encoded once; the returned `LATENT` is sized to that
   same grid, so the cond stream and the sampled target share a resolution.
 - **`strength`** — scales the trained cond effect. `1.0` = as trained. Raise to
   push harder toward the reference, lower to loosen.
-- **`target_megapixels`** (optional) — output size in megapixels for the returned
-  latent and the cond encode. `1.0` (default) keeps generation on the ~1MP
-  distribution Anima was trained at; `0` keeps the input's native resolution
-  (still snapped to the VAE/patch grid). Feed the `LATENT` output into the
-  KSampler's `latent_image`.
+- **`target_megapixels`** (optional) — max output size in megapixels for the
+  returned latent and the cond encode. `1.0` (default) keeps generation on the
+  ~1MP distribution Anima was trained at by downscaling anything larger; a source
+  already below the cap is left at its native resolution (never upscaled). `0`
+  keeps the input's native resolution (still snapped to the VAE/patch grid). Feed
+  the `LATENT` output into the KSampler's `latent_image`.
 - **`cond_scale_override`** (optional) — replace the checkpoint's trained
   `cond_scale` outright (before `strength`); `0` = keep the trained value.
 

nodes.py

@@ -32,9 +32,12 @@ def _vae_spatial(vae):
 
 
 def _resize_to_megapixels(image, vae, target_mp):
-    """Resize an IMAGE ``[B,H,W,C]`` (in [0,1]) to ~``target_mp`` megapixels,
-    aspect-preserving, snapping each side to ``vae_spatial * patch(2)`` so the
-    resulting latent has even dims (cosmos ``patch_spatial=2``).
+    """Resize an IMAGE ``[B,H,W,C]`` (in [0,1]) to at most ``target_mp``
+    megapixels, aspect-preserving, snapping each side to ``vae_spatial *
+    patch(2)`` so the resulting latent has even dims (cosmos ``patch_spatial=2``).
+
+    ``target_mp`` is a MAX cap: a source already below it is left at its native
+    resolution (only snapped) rather than upscaled.
 
     ``target_mp <= 0`` means keep the native resolution (still snapped, so the
     VAE/patch grid is clean). Returns the resized image ``[B,H,W,C]``.
@@ -44,7 +47,9 @@ def _resize_to_megapixels(image, vae, target_mp):
     mult_h, mult_w = sh * 2, sw * 2
 
     if target_mp and target_mp > 0:
-        scale = (target_mp * 1_000_000 / float(h * w)) ** 0.5
+        # target_mp is a MAX cap: only downscale when the source exceeds it,
+        # never upscale a smaller source (clamp scale to <= 1.0).
+        scale = min(1.0, (target_mp * 1_000_000 / float(h * w)) ** 0.5)
         new_h, new_w = h * scale, w * scale
     else:
         new_h, new_w = float(h), float(w)

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-easycontrol-ksamplercompat"
 description = "KSampler-compatible Anima EasyControl image conditioning for ComfyUI. A single model-patch node (MODEL + VAE + IMAGE -> MODEL) that feeds a reference image into the Anima DiT's frozen extended self-attention stream and returns a patched MODEL for the stock KSampler — no dedicated sampler node. Reimplements anima_lora's EasyControl inference path against ComfyUI's native Anima/Cosmos DiT backbone (split q/k/v projections). EasyControl checkpoints go in models/loras/. Typical use: grayscale/lineart -> color (colorization)."
-version = "0.1.4"
+version = "0.1.5"
 license = { file = "LICENSE" }
 dependencies = []