fix: correct Math model output transpose from [C,B,T] to [B,T,C]
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This commit is contained in:
2026-07-17 11:38:24 +00:00
parent 2fceca847f
commit 6c123b7231
+13 -140
View File
@@ -392,156 +392,29 @@ func preprocessMath(img image.Image) ([]float32, error) {
} }
func decodeMathFromOutput(output []float32) string { func decodeMathFromOutput(output []float32) string {
// Math 模型输出固定: numChars=51, batch=1, timesteps=19, total=969 // Math 模型输出: [C, B, T] = [51, 1, 19]
// 可能的格式: [51, 1, 19] [19, 1, 51] // 需要转置为 [B, T, C] = [1, 19, 51]
numChars := 51 numChars := 51
batch := 1 batch := 1
timesteps := 19 timesteps := 19
totalElems := numChars * batch * timesteps // 969
if len(output) != totalElems { if len(output) != numChars*batch*timesteps {
// 尝试推断 timesteps
timesteps = len(output) / numChars timesteps = len(output) / numChars
if timesteps <= 0 { if timesteps <= 0 {
return "" return ""
} }
} }
// 尝试两种格式 // 转置: [C, B, T] -> [B, T, C]
// 格式1: [T, B, C] = [19, 1, 51] // output[c*batch*timesteps + b*timesteps + t] -> data[b*timesteps*numChars + t*numChars + c]
result1 := decodeMathFormat(output, timesteps, batch, numChars, true) data := make([]float32, batch*timesteps*numChars)
// 格式2: [C, B, T] = [51, 1, 19] for c := 0; c < numChars; c++ {
result2 := decodeMathFormat(output, timesteps, batch, numChars, false) for b := 0; b < batch; b++ {
for t := 0; t < timesteps; t++ {
// 返回更长的结果(更可能是正确的) srcIdx := c*batch*timesteps + b*timesteps + t
if len(result1) >= len(result2) { dstIdx := b*timesteps*numChars + t*numChars + c
return result1 if srcIdx < len(output) && dstIdx < len(data) {
} data[dstIdx] = output[srcIdx]
return result2
}
func decodeMathFormat(output []float32, timesteps, batch, numChars int, isTBC bool) string {
var data []float32
if isTBC {
// 格式: [T, B, C] -> [B, T, C]
data = make([]float32, batch*timesteps*numChars)
for t := 0; t < timesteps; t++ {
for b := 0; b < batch; b++ {
for c := 0; c < numChars; c++ {
srcIdx := t*batch*numChars + b*numChars + c
dstIdx := b*timesteps*numChars + t*numChars + c
if srcIdx < len(output) && dstIdx < len(data) {
data[dstIdx] = output[srcIdx]
}
}
}
}
} else {
// 格式: [C, B, T] -> [B, T, C]
data = make([]float32, batch*timesteps*numChars)
for c := 0; c < numChars; c++ {
for b := 0; b < batch; b++ {
for t := 0; t < timesteps; t++ {
srcIdx := c*batch*timesteps + b*timesteps + t
dstIdx := b*timesteps*numChars + t*numChars + c
if srcIdx < len(output) && dstIdx < len(data) {
data[dstIdx] = output[srcIdx]
}
}
}
}
}
// CTC 解码
result := ""
lastIdx := -1
for t := 0; t < timesteps; t++ {
maxIdx := 0
maxProb := float32(-math.MaxFloat32)
for c := 0; c < numChars; c++ {
idx := t*numChars + c
if idx < len(data) && data[idx] > maxProb {
maxProb = data[idx]
maxIdx = c
}
}
if maxIdx != 0 && maxIdx != lastIdx {
if maxIdx-1 < len(mathChars) {
result += string(mathChars[maxIdx-1])
}
}
lastIdx = maxIdx
}
return result
}
func decodeMath(output []float32, outputShape []int64) string {
// 原版逻辑:
// if preds.shape[1] == 1: # Batch size is 1 at dim 1 implies [T, B, C]
// preds = np.transpose(preds, (1, 0, 2)) # [B, T, C]
// preds_idx = np.argmax(preds, axis=2) # [B, T]
if len(outputShape) < 3 || len(output) == 0 {
return ""
}
// 输出可能是 [T, B, C] 或 [C, B, T]
// 判断依据:如果 shape[1] == 1,说明 batch 在中间,格式是 [T, B, C]
// 否则格式是 [C, B, T] 或 [num_chars, batch, timesteps]
dim0 := int(outputShape[0])
dim1 := int(outputShape[1])
dim2 := int(outputShape[2])
// 处理动态维度
if dim0 <= 0 { dim0 = 51 }
if dim1 <= 0 { dim1 = 1 }
if dim2 <= 0 { dim2 = len(output) / (dim0 * dim1) }
var timesteps, batch, numChars int
var data []float32
// 判断输出格式
if dim1 == 1 {
// 格式: [T, B, C] = [19, 1, 51]
// 需要转置为 [B, T, C] = [1, 19, 51]
timesteps = dim0
batch = dim1
numChars = dim2
data = make([]float32, batch*timesteps*numChars)
for t := 0; t < timesteps; t++ {
for b := 0; b < batch; b++ {
for c := 0; c < numChars; c++ {
srcIdx := t*batch*numChars + b*numChars + c
dstIdx := b*timesteps*numChars + t*numChars + c
if srcIdx < len(output) && dstIdx < len(data) {
data[dstIdx] = output[srcIdx]
}
}
}
}
} else {
// 格式: [C, B, T] = [51, 1, 19]
// 需要转置为 [B, T, C] = [1, 19, 51]
numChars = dim0
batch = dim1
timesteps = dim2
data = make([]float32, batch*timesteps*numChars)
for c := 0; c < numChars; c++ {
for b := 0; b < batch; b++ {
for t := 0; t < timesteps; t++ {
srcIdx := c*batch*timesteps + b*timesteps + t
dstIdx := b*timesteps*numChars + t*numChars + c
if srcIdx < len(output) && dstIdx < len(data) {
data[dstIdx] = output[srcIdx]
}
} }
} }
} }