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// Copyright 2013 Google Inc. All Rights Reserved.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// See the License for the specific language governing permissions and
// limitations under the License.
// Author: (Dick Sites)
#include <vector>
#include "../public/compact_lang_det.h" // For CLDHints, ResultChunkVector
#include "integral_types.h"
#include "lang_script.h"
namespace CLD2 {
// Internal use flags
static const int kCLDFlagFinish = 1;
static const int kCLDFlagSqueeze = 2;
static const int kCLDFlagRepeats = 4;
static const int kCLDFlagTop40 = 8;
static const int kCLDFlagShort = 16;
static const int kCLDFlagHint = 32;
static const int kCLDFlagUseWords = 64;
static const int kCLDFlagUNUSED = 128;
// Public use flags, debug output controls, defined in compact_lang_det.h
// 0x0100 and above
Flag meanings:
Flags are used in the context of a recursive call from Detect to itself,
trying to deal in a more restrictive way with input that was not reliably
identified in the top-level call.
Finish -- Do not further recurse; return whatever result ensues, even if it is
unreliable. Typically set in any recursive call to take a second try
on unreliable text.
Squeeze -- For each text run, do an inplace cheapsqueeze to remove chunks of
highly repetitive text and chunks of text with too many 1- and
2-letter words. This avoids scoring repetitive or useless non-text
crap in large files such bogus JPEGs within an HTML file.
Repeats -- When scoring a text run, do a cheap prediction of each character
and do not score a unigram/quadgram if the last character of same is
correctly predicted. This is a slower, finer-grained form of
cheapsqueeze, typically used when the first pass got unreliable
Top40 -- Restrict the set of scored languages to the Google "Top 40", which is
actually 38 languages. This gets rid of about 110 languages that
represent about 0.7% of the web. Typically used when the first pass
got unreliable results.
Short -- DEPRICATED, unused
Hint -- EXPERIMENTAL flag for to indicate a language
hint supplied in parameter plus_one.
UseWords -- In additon to scoring quad/uni/nil-grams, score complete words
Tentative decision logic:
In the middle of first pass -- After 4KB of text, look at the front 256 bytes
of every full 4KB buffer. If it compresses very well (say 3:1) or has
lots of spaces (say 1 of every 4 bytes), assume that the input is
large and contains lots of bogus non-text. Recurse, passing the
Squeeze flag to strip out chunks of this non-text.
At the end of the first pass --
If the top language is reliable and >= 70% of the document, return.
Else if the top language is reliable and top+2nd >= say 94%, return.
Else, either the top language is not reliable or there is a lot of
other crap.
// Scan interchange-valid UTF-8 bytes and detect most likely language,
// or set of languages.
// Design goals:
// Skip over big stretches of HTML tags
// Able to return ranges of different languages
// Relatively small tables and relatively fast processing
// Thread safe
typedef struct {
int perscript_count;
const Language* perscript_lang;
} PerScriptPair;
typedef struct {
// Constants for hashing 4-7 byte quadgram to 32 bits
const int kQuadHashB4Shift;
const int kQuadHashB4bShift;
const int kQuadHashB5Shift;
const int kQuadHashB5bShift;
// Constants for hashing 32 bits to kQuadKeyTable subscript/key
const int kHashvalToSubShift;
const uint32 kHashvalToSubMask;
const int kHashvalToKeyShift;
const uint32 kHashvalToKeyMask;
const int kHashvalAssociativity;
// Pointers to the actual tables
const PerScriptPair* kPerScriptPair;
const uint16* kQuadKeyTable;
const uint32* kQuadValueTable;
} LangDetObj;
// For HTML documents, tags are skipped, along with <script> ... </script>
// and <style> ... </style> sequences, and entities are expanded.
// We distinguish between bytes of the raw input buffer and bytes of non-tag
// text letters. Since tags can be over 50% of the bytes of an HTML Page,
// and are nearly all seven-bit ASCII English, we prefer to distinguish
// language mixture fractions based on just the non-tag text.
// Inputs: text and text_length
// is_plain_text if true says to NOT parse/skip HTML tags nor entities
// Outputs:
// language3 is an array of the top 3 languages or UNKNOWN_LANGUAGE
// percent3 is an array of the text percentages 0..100 of the top 3 languages
// normalized_score3 is an array of internal scores, normalized to the
// average score for each language over a body of training text. A
// normalized score significantly away from 1.0 indicates very skewed text
// or gibberish.
// text_bytes is the amount of non-tag/letters-only text found
// is_reliable set true if the returned Language is at least 2**30 times more
// probable then the second-best Language
// Return value: the most likely Language for the majority of the input text
// Length 0 input and text with no reliable letter sequences returns
// Subsetting: For fast detection over large documents, these routines will
// only scan up to a fixed limit (currently 160KB of non-tag letters).
Language DetectLanguageSummaryV2(
const char* buffer,
int buffer_length,
bool is_plain_text,
const CLDHints* cld_hints,
bool allow_extended_lang,
int flags,
Language plus_one,
Language* language3,
int* percent3,
double* normalized_score3,
ResultChunkVector* resultchunkvector,
int* text_bytes,
bool* is_reliable);
// For unit testing:
// Remove portions of text that have a high density of spaces, or that are
// overly repetitive, squeezing the remaining text in-place to the front
// of the input buffer.
// Return the new, possibly-shorter length
int CheapSqueezeInplace(char* isrc, int srclen, int ichunksize);
} // End namespace CLD2