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TAV: iS tHiS aN iMpRoVeMeNt¿

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minjaesong
2025-10-16 09:24:21 +09:00
parent cc2f3e4d57
commit 0cf1173dd6
3 changed files with 110 additions and 46 deletions
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30
tsvm_core/src/net/torvald/tsvm/GraphicsJSR223Delegate.kt
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@@ -4542,6 +4542,13 @@ class GraphicsJSR223Delegate(private val vm: VM) {
val framesPerSubband = numFrames shr temporalLevels // numFrames / 2^temporalLevels
// Safety check: ensure we have enough frames for the temporal levels
// Minimum frames needed = 2^temporalLevels
if (framesPerSubband == 0) {
// Not enough frames for this many temporal levels - treat all as base level
return 0
}
// Determine which temporal subband this frame belongs to
val subbandIdx = frameIdx / framesPerSubband
@@ -4863,6 +4870,7 @@ class GraphicsJSR223Delegate(private val vm: VM) {
0x00 -> { // TAV_MODE_SKIP
// Copy 280x224 tile from previous frame to current frame
tavCopyTileRGB(tileX, tileY, currentRGBAddr, prevRGBAddr, width, height)
println("SKIP tile at frame $frameCount")
dbgOut["frameMode"] = "S"
}
0x01 -> { // TAV_MODE_INTRA
@@ -4870,7 +4878,7 @@ class GraphicsJSR223Delegate(private val vm: VM) {
readPtr = tavDecodeDWTIntraTileRGB(qIndex, qYGlobal, channelLayout, readPtr, tileX, tileY, currentRGBAddr,
width, height, qY, qCo, qCg,
waveletFilter, decompLevels, isLossless, tavVersion, isMonoblock, frameCount)
dbgOut["frameMode"] = " "
dbgOut["frameMode"] = "I"
}
0x02 -> { // TAV_MODE_DELTA (with optional Haar wavelet)
// Coefficient delta encoding for efficient P-frames
@@ -6275,7 +6283,13 @@ class GraphicsJSR223Delegate(private val vm: VM) {
spatialFilter: Int = 1,
spatialLevels: Int = 6,
temporalLevels: Int = 2
): Int {
): Array<Any> {
val dbgOut = HashMap<String, Any>()
dbgOut["qY"] = qYGlobal
dbgOut["qCo"] = qCoGlobal
dbgOut["qCg"] = qCgGlobal
dbgOut["frameMode"] = "G"
val numPixels = width * height
// Step 1: Decompress unified GOP block
@@ -6294,7 +6308,7 @@ class GraphicsJSR223Delegate(private val vm: VM) {
}
} catch (e: Exception) {
println("ERROR: Zstd decompression failed: ${e.message}")
return 0
return arrayOf(0, dbgOut)
}
// Step 2: Postprocess unified block to per-frame coefficients
@@ -6318,10 +6332,10 @@ class GraphicsJSR223Delegate(private val vm: VM) {
val temporalLevel = getTemporalSubbandLevel(t, gopSize, temporalLevels)
val temporalScale = getTemporalQuantizerScale(temporalLevel)
// Apply temporal scaling to base quantizers
val baseQY = (qYGlobal * temporalScale).coerceIn(1.0f, 255.0f)
val baseQCo = (qCoGlobal * temporalScale).coerceIn(1.0f, 255.0f)
val baseQCg = (qCgGlobal * temporalScale).coerceIn(1.0f, 255.0f)
// Apply temporal scaling to base quantizers for each channel
val baseQY = (qYGlobal * temporalScale).coerceIn(1.0f, 4096.0f)
val baseQCo = (qCoGlobal * temporalScale).coerceIn(1.0f, 4096.0f)
val baseQCg = (qCgGlobal * temporalScale).coerceIn(1.0f, 4096.0f)
// Use existing perceptual dequantization for spatial weighting
dequantiseDWTSubbandsPerceptual(
@@ -6389,7 +6403,7 @@ class GraphicsJSR223Delegate(private val vm: VM) {
}
}
return gopSize
return arrayOf(gopSize, dbgOut)
}
// Biorthogonal 13/7 wavelet inverse 1D transform