mirror of
https://github.com/opencv/opencv.git
synced 2024-11-28 05:06:29 +08:00
Fixed several issues found by static analysis
This commit is contained in:
parent
d8b1fc45aa
commit
a079c2eb7c
@ -238,7 +238,7 @@ public:
|
||||
|
||||
EltwiseInvoker(EltwiseLayerInt8Impl& self_)
|
||||
: self(self_)
|
||||
, nsrcs(0), dst(0), buf(0), nstripes(0), activ(0), channels(0)
|
||||
, nsrcs(0), dst(0), buf(0), nstripes(0), activLUT(0), activ(0), channels(0)
|
||||
, planeSize(0), offset(0)
|
||||
{}
|
||||
|
||||
@ -345,7 +345,8 @@ public:
|
||||
int8_t* dstptr0 = dst->ptr<int8_t>();
|
||||
float* bufptr0 = buf->ptr<float>();
|
||||
int blockSize0 = 1 << 12;
|
||||
|
||||
CV_Assert(op != PROD || zeropointsptr);
|
||||
CV_Assert((op != PROD && op != SUM) || coeffsptr);
|
||||
for (size_t ofs = stripeStart; ofs < stripeEnd; )
|
||||
{
|
||||
int sampleIdx = (int)(ofs / planeSize);
|
||||
|
@ -2023,7 +2023,9 @@ void ONNXImporter::parseUnsqueeze(LayerParams& layerParams, const opencv_onnx::N
|
||||
}
|
||||
CV_Assert(axes.getIntValue(axes.size()-1) <= dims.size());
|
||||
for (int j = 0; j < axes.size(); j++) {
|
||||
dims.insert(dims.begin() + axes.getIntValue(j), 1);
|
||||
const int idx = axes.getIntValue(j);
|
||||
CV_Assert(idx <= dims.size());
|
||||
dims.insert(dims.begin() + idx, 1);
|
||||
}
|
||||
|
||||
Mat out = input.reshape(0, dims);
|
||||
|
@ -142,6 +142,7 @@ private:
|
||||
{64.0f, 96.0f},
|
||||
{128.0f, 192.0f, 256.0f}
|
||||
};
|
||||
CV_Assert(min_sizes.size() == feature_map_sizes.size()); // just to keep vectors in sync
|
||||
const std::vector<int> steps = { 8, 16, 32, 64 };
|
||||
|
||||
// Generate priors
|
||||
|
@ -45,8 +45,8 @@ public:
|
||||
double match(InputArray _face_feature1, InputArray _face_feature2, int dis_type) const override
|
||||
{
|
||||
Mat face_feature1 = _face_feature1.getMat(), face_feature2 = _face_feature2.getMat();
|
||||
face_feature1 /= norm(face_feature1);
|
||||
face_feature2 /= norm(face_feature2);
|
||||
normalize(face_feature1, face_feature1);
|
||||
normalize(face_feature2, face_feature2);
|
||||
|
||||
if(dis_type == DisType::FR_COSINE){
|
||||
return sum(face_feature1.mul(face_feature2))[0];
|
||||
|
@ -881,6 +881,8 @@ void QRCodeEncoderImpl::findAutoMaskType()
|
||||
total_modules += 1;
|
||||
}
|
||||
}
|
||||
if (total_modules == 0)
|
||||
continue; // TODO: refactor, extract functions to reduce complexity
|
||||
int modules_percent = dark_modules * 100 / total_modules;
|
||||
int lower_bound = 45;
|
||||
int upper_bound = 55;
|
||||
|
Loading…
Reference in New Issue
Block a user