Merge pull request #466 from stweil/opencl

Fix some typos (found by codespell)
This commit is contained in:
zdenop 2016-11-22 09:11:24 +01:00 committed by GitHub
commit cdc2863b48
11 changed files with 15 additions and 15 deletions

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@ -24,7 +24,7 @@ So, the steps for making Tesseract are:
You need to install at least English language and OSD data files to TESSDATA_PREFIX You need to install at least English language and OSD data files to TESSDATA_PREFIX
directory. You can retrieve single file with tools like [wget](https://www.gnu.org/software/wget/), [curl](https://curl.haxx.se/), [GithubDownloader](https://github.com/intezer/GithubDownloader) or browser. directory. You can retrieve single file with tools like [wget](https://www.gnu.org/software/wget/), [curl](https://curl.haxx.se/), [GithubDownloader](https://github.com/intezer/GithubDownloader) or browser.
All language data files can be retrieved from git repository (usefull only for packagers!): All language data files can be retrieved from git repository (useful only for packagers!):
$ git clone https://github.com/tesseract-ocr/tessdata.git tesseract-ocr.tessdata $ git clone https://github.com/tesseract-ocr/tessdata.git tesseract-ocr.tessdata

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@ -209,7 +209,7 @@ class LSTMRecognizer {
// If label_threshold is positive, uses it for making the labels, otherwise // If label_threshold is positive, uses it for making the labels, otherwise
// uses standard ctc. Returned in scale_factor is the reduction factor // uses standard ctc. Returned in scale_factor is the reduction factor
// between the image and the output coords, for computing bounding boxes. // between the image and the output coords, for computing bounding boxes.
// If re_invert is true, the input is inverted back to its orginal // If re_invert is true, the input is inverted back to its original
// photometric interpretation if inversion is attempted but fails to // photometric interpretation if inversion is attempted but fails to
// improve the results. This ensures that outputs contains the correct // improve the results. This ensures that outputs contains the correct
// forward outputs for the best photometric interpretation. // forward outputs for the best photometric interpretation.
@ -351,7 +351,7 @@ class LSTMRecognizer {
// The unicharset. Only the unicharset element is serialized. // The unicharset. Only the unicharset element is serialized.
// Has to be a CCUtil, so Dict can point to it. // Has to be a CCUtil, so Dict can point to it.
CCUtil ccutil_; CCUtil ccutil_;
// For backward compatability, recoder_ is serialized iff // For backward compatibility, recoder_ is serialized iff
// training_flags_ & TF_COMPRESS_UNICHARSET. // training_flags_ & TF_COMPRESS_UNICHARSET.
// Further encode/decode ccutil_.unicharset's ids to simplify the unicharset. // Further encode/decode ccutil_.unicharset's ids to simplify the unicharset.
UnicharCompress recoder_; UnicharCompress recoder_;

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@ -91,7 +91,7 @@ struct RecodeNode {
bool start_of_word; bool start_of_word;
// True if this represents a valid candidate end of word position. Does not // True if this represents a valid candidate end of word position. Does not
// necessarily mark the end of a word, since a word can be extended beyond a // necessarily mark the end of a word, since a word can be extended beyond a
// candidiate end by a continuation, eg 'the' continues to 'these'. // candidate end by a continuation, eg 'the' continues to 'these'.
bool end_of_word; bool end_of_word;
// True if this is a duplicate of prev in all respects. Some training modes // True if this is a duplicate of prev in all respects. Some training modes
// allow the network to output duplicate characters and crush them with CTC, // allow the network to output duplicate characters and crush them with CTC,

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@ -142,7 +142,7 @@ bool Series::Backward(bool debug, const NetworkIO& fwd_deltas,
} }
// Splits the series after the given index, returning the two parts and // Splits the series after the given index, returning the two parts and
// deletes itself. The first part, upto network with index last_start, goes // deletes itself. The first part, up to network with index last_start, goes
// into start, and the rest goes into end. // into start, and the rest goes into end.
void Series::SplitAt(int last_start, Series** start, Series** end) { void Series::SplitAt(int last_start, Series** start, Series** end) {
*start = NULL; *start = NULL;

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@ -77,7 +77,7 @@ class Series : public Plumbing {
NetworkIO* back_deltas); NetworkIO* back_deltas);
// Splits the series after the given index, returning the two parts and // Splits the series after the given index, returning the two parts and
// deletes itself. The first part, upto network with index last_start, goes // deletes itself. The first part, up to network with index last_start, goes
// into start, and the rest goes into end. // into start, and the rest goes into end.
void SplitAt(int last_start, Series** start, Series** end); void SplitAt(int last_start, Series** start, Series** end);

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@ -32,7 +32,7 @@ enum LossType {
}; };
// Simple class to hold the tensor shape that is known at network build time // Simple class to hold the tensor shape that is known at network build time
// and the LossType of the loss funtion. // and the LossType of the loss function.
class StaticShape { class StaticShape {
public: public:
StaticShape() StaticShape()

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@ -38,7 +38,7 @@ bool StrideMap::Index::IsLast(FlexDimensions dimension) const {
return MaxIndexOfDim(dimension) == indices_[dimension]; return MaxIndexOfDim(dimension) == indices_[dimension];
} }
// Given that the dimensions upto and including dim-1 are valid, returns the // Given that the dimensions up to and including dim-1 are valid, returns the
// maximum index for dimension dim. // maximum index for dimension dim.
int StrideMap::Index::MaxIndexOfDim(FlexDimensions dim) const { int StrideMap::Index::MaxIndexOfDim(FlexDimensions dim) const {
int max_index = stride_map_->shape_[dim] - 1; int max_index = stride_map_->shape_[dim] - 1;

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@ -69,7 +69,7 @@ class StrideMap {
bool IsValid() const; bool IsValid() const;
// Returns true if the index of the given dimension is the last. // Returns true if the index of the given dimension is the last.
bool IsLast(FlexDimensions dimension) const; bool IsLast(FlexDimensions dimension) const;
// Given that the dimensions upto and including dim-1 are valid, returns the // Given that the dimensions up to and including dim-1 are valid, returns the
// maximum index for dimension dim. // maximum index for dimension dim.
int MaxIndexOfDim(FlexDimensions dim) const; int MaxIndexOfDim(FlexDimensions dim) const;
// Adds the given offset to the given dimension. Returns true if the result // Adds the given offset to the given dimension. Returns true if the result

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@ -163,7 +163,7 @@ const int kDoubleFlag = 128;
// Writes to the given file. Returns false in case of error. // Writes to the given file. Returns false in case of error.
bool WeightMatrix::Serialize(bool training, TFile* fp) const { bool WeightMatrix::Serialize(bool training, TFile* fp) const {
// For backward compatability, add kDoubleFlag to mode to indicate the doubles // For backward compatibility, add kDoubleFlag to mode to indicate the doubles
// format, without errs, so we can detect and read old format weight matrices. // format, without errs, so we can detect and read old format weight matrices.
uinT8 mode = (int_mode_ ? kInt8Flag : 0) | uinT8 mode = (int_mode_ ? kInt8Flag : 0) |
(use_ada_grad_ ? kAdaGradFlag : 0) | kDoubleFlag; (use_ada_grad_ ? kAdaGradFlag : 0) | kDoubleFlag;
@ -202,7 +202,7 @@ bool WeightMatrix::DeSerialize(bool training, bool swap, TFile* fp) {
} }
// As DeSerialize, but reads an old (float) format WeightMatrix for // As DeSerialize, but reads an old (float) format WeightMatrix for
// backward compatability. // backward compatibility.
bool WeightMatrix::DeSerializeOld(bool training, bool swap, TFile* fp) { bool WeightMatrix::DeSerializeOld(bool training, bool swap, TFile* fp) {
GENERIC_2D_ARRAY<float> float_array; GENERIC_2D_ARRAY<float> float_array;
if (int_mode_) { if (int_mode_) {

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@ -100,7 +100,7 @@ class WeightMatrix {
// If swap is true, assumes a big/little-endian swap is needed. // If swap is true, assumes a big/little-endian swap is needed.
bool DeSerialize(bool training, bool swap, TFile* fp); bool DeSerialize(bool training, bool swap, TFile* fp);
// As DeSerialize, but reads an old (float) format WeightMatrix for // As DeSerialize, but reads an old (float) format WeightMatrix for
// backward compatability. // backward compatibility.
bool DeSerializeOld(bool training, bool swap, TFile* fp); bool DeSerializeOld(bool training, bool swap, TFile* fp);
// Computes matrix.vector v = Wu. // Computes matrix.vector v = Wu.

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@ -3163,7 +3163,7 @@ ds_device OpenclDevice::getDeviceSelection( ) {
// cleanup // cleanup
// TODO: call destructor for profile object? // TODO: call destructor for profile object?
bool overrided = false; bool overridden = false;
char *overrideDeviceStr = getenv("TESSERACT_OPENCL_DEVICE"); char *overrideDeviceStr = getenv("TESSERACT_OPENCL_DEVICE");
if (overrideDeviceStr != NULL) { if (overrideDeviceStr != NULL) {
int overrideDeviceIdx = atoi(overrideDeviceStr); int overrideDeviceIdx = atoi(overrideDeviceStr);
@ -3173,7 +3173,7 @@ ds_device OpenclDevice::getDeviceSelection( ) {
"%i)\n", "%i)\n",
overrideDeviceStr, overrideDeviceIdx); overrideDeviceStr, overrideDeviceIdx);
bestDeviceIdx = overrideDeviceIdx - 1; bestDeviceIdx = overrideDeviceIdx - 1;
overrided = true; overridden = true;
} else { } else {
printf( printf(
"[DS] Ignoring invalid TESSERACT_OPENCL_DEVICE=%s ([1,%i] are " "[DS] Ignoring invalid TESSERACT_OPENCL_DEVICE=%s ([1,%i] are "
@ -3182,7 +3182,7 @@ ds_device OpenclDevice::getDeviceSelection( ) {
} }
} }
if (overrided) { if (overridden) {
printf("[DS] Overridden Device[%i]: \"%s\" (%s)\n", bestDeviceIdx + 1, printf("[DS] Overridden Device[%i]: \"%s\" (%s)\n", bestDeviceIdx + 1,
profile->devices[bestDeviceIdx].oclDeviceName, profile->devices[bestDeviceIdx].oclDeviceName,
profile->devices[bestDeviceIdx].type == DS_DEVICE_OPENCL_DEVICE profile->devices[bestDeviceIdx].type == DS_DEVICE_OPENCL_DEVICE