diff options
Diffstat (limited to 'cnn_v3/docs/HOWTO.md')
| -rw-r--r-- | cnn_v3/docs/HOWTO.md | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/cnn_v3/docs/HOWTO.md b/cnn_v3/docs/HOWTO.md index 5c5cc2a..a1a5707 100644 --- a/cnn_v3/docs/HOWTO.md +++ b/cnn_v3/docs/HOWTO.md @@ -90,7 +90,7 @@ Outputs are named from the `outputs` vector passed to the constructor: ``` outputs[0] → feat_tex0 (rgba32uint: albedo.rgb, normal.xy, depth, depth_grad.xy) -outputs[1] → feat_tex1 (rgba32uint: mat_id, prev.rgb, mip1.rgb, mip2.rgb, shadow, transp) +outputs[1] → feat_tex1 (rgba32uint: mat_id, prev.rgb, mip1.rgb, mip2.rgb, dif, transp) ``` --- @@ -285,7 +285,7 @@ python3 train_cnn_v3.py \ Applied per-sample in `cnn_v3_utils.apply_channel_dropout()`: - Geometric channels (normal, depth, depth_grad) zeroed with `p=channel_dropout_p` -- Context channels (mat_id, shadow, transp) with `p≈0.2` +- Context channels (mat_id, dif, transp) with `p≈0.2` - Temporal channels (prev.rgb) with `p=0.5` This ensures the network works for both full G-buffer and photo-only inputs. @@ -474,7 +474,7 @@ auto gview = std::make_shared<GBufViewEffect>(ctx, | 1 | `nrm.y` remap→[0,1] | `depth` (inverted) | `dzdx` ×20+0.5 | `dzdy` ×20+0.5 | | 2 | `mat_id` | `prev.r` | `prev.g` | `prev.b` | | 3 | `mip1.r` | `mip1.g` | `mip1.b` | `mip2.r` | -| 4 | `mip2.g` | `mip2.b` | `shadow` | `transp` | +| 4 | `mip2.g` | `mip2.b` | `dif` | `transp` | All channels displayed as grayscale. 1-pixel gray grid lines separate cells. Dark background for out-of-range cells. @@ -535,7 +535,7 @@ No sampler — all reads use `textureLoad()` (integer texel coordinates). Packs channels identically to `gbuf_pack.wgsl`: - `feat_tex0`: `pack2x16float(alb.rg)`, `pack2x16float(alb.b, nrm.x)`, `pack2x16float(nrm.y, depth)`, `pack2x16float(dzdx, dzdy)` -- `feat_tex1`: `pack4x8unorm(matid,0,0,0)`, `pack4x8unorm(mip1.rgb, mip2.r)`, `pack4x8unorm(mip2.gb, shadow, transp)` +- `feat_tex1`: `pack4x8unorm(matid,0,0,0)`, `pack4x8unorm(mip1.rgb, mip2.r)`, `pack4x8unorm(mip2.gb, dif, transp)` - Depth gradients: central differences on depth R channel - Mip1 / Mip2: box2 (2×2) / box4 (4×4) average filter on albedo |