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- Add --cnn-version <1|2> flag to select between CNN v1 and v2
- Implement beat_phase modulation for dynamic blend in both CNN effects
- Fix CNN v2 per-layer uniform buffer sharing (each layer needs own buffer)
- Fix CNN v2 y-axis orientation to match render pass convention
- Add Scene1Effect as base visual layer to test_demo timeline
- Reorganize CNN v2 shaders into cnn_v2/ subdirectory
- Update asset paths and documentation for new shader organization
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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Root cause: After swapping init/resize order, effects with Renderer3D crashed
because resize() called before init() tried to use uninitialized GPU resources.
Changes:
- Add guards in FlashCubeEffect::resize() and Hybrid3DEffect::resize() to
check ctx_.device before calling renderer_.resize()
- Remove lazy initialization remnants from CircleMaskEffect and CNNEffect
- Register auxiliary textures directly in init() (width_/height_ already set)
- Remove ensure_texture() methods and texture_initialized_ flags
All 36 tests passing. Demo runs without crashes.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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Prevents init/resize ordering bug and avoids unnecessary reallocation.
Changes:
- Auxiliary textures created on first use (compute/update_bind_group)
- Added ensure_texture() methods to defer registration until resize()
- Added early return in resize() if dimensions unchanged
- Removed texture registration from init() methods
Benefits:
- No reallocation on window resize if dimensions match
- Texture created with correct dimensions from start
- Memory saved if effect never renders
Tests: All 36 tests passing
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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Auxiliary textures were created during init() using default dimensions
(1280x720) before resize() was called with actual window size. This
caused compute shaders to receive uniforms with correct resolution but
render to wrong-sized textures.
Changes:
- Add MainSequence::resize_auxiliary_texture() to recreate textures
- Override resize() in CircleMaskEffect to resize circle_mask texture
- Override resize() in CNNEffect to resize captured_frame texture
- Bind groups are recreated with new texture views after resize
Tests: All 36 tests passing
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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Root cause: Uniform buffers created but not initialized before bind group
creation, causing undefined UV coordinates in circle_mask_compute.wgsl.
Changes:
- Add get_common_uniforms() helper to Effect base class
- Refactor render()/compute() signatures: 5 params → CommonPostProcessUniforms&
- Fix uninitialized uniforms in CircleMaskEffect and CNNEffect
- Update all 19 effect implementations and headers
- Fix WGSL syntax error in FlashEffect (u.audio_intensity → audio_intensity)
- Update test files (test_sequence.cc)
Benefits:
- Cleaner API: construct uniforms once per frame, reuse across effects
- More maintainable: CommonPostProcessUniforms changes need no call site updates
- Fixes UV coordinate bug in circle_mask_compute.wgsl
All 36 tests passing (100%)
handoff(Claude): Effect API refactor complete
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Implements automatic layer chaining and generic framebuffer capture API for
multi-layer neural network effects with proper original input preservation.
Key changes:
- Effect::needs_framebuffer_capture() - generic API for pre-render capture
- MainSequence: auto-capture to "captured_frame" auxiliary texture
- CNNEffect: multi-layer support via layer_index/total_layers params
- seq_compiler: expands "layers=N" to N chained effect instances
- Shader: @binding(4) original_input available to all layers
- Training: generates layer switches and original input binding
- Blend: mix(original, result, blend_amount) uses layer 0 input
Timeline syntax: CNNEffect layers=3 blend=0.7
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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Implements multi-layer convolutional neural network shader for stylized
post-processing of 3D rendered scenes:
**Core Components:**
- CNNEffect: C++ effect class with single-layer rendering (expandable to multi-pass)
- Modular WGSL snippets: cnn_activation, cnn_conv3x3/5x5/7x7, cnn_weights_generated
- Placeholder identity-like weights for initial testing (to be replaced by trained weights)
**Architecture:**
- Flexible kernel sizes (3×3, 5×5, 7×7) via separate snippet files
- ShaderComposer integration (#include resolution)
- Residual connections (input + processed output)
- Supports parallel convolutions (design ready, single conv implemented)
**Size Impact:**
- ~3-4 KB shader code (snippets + main shader)
- ~2-4 KB weights (depends on network architecture when trained)
- Total: ~5-8 KB (acceptable for 64k demo)
**Testing:**
- CNNEffect added to test_demo_effects.cc
- 36/36 tests passing (100%)
**Next Steps:**
- Training script (scripts/train_cnn.py) to generate real weights
- Multi-layer rendering with ping-pong textures
- Weight quantization for size optimization
handoff(Claude): CNN effect foundation complete, ready for training integration
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