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<div class="title">convert_caffe_image_db.cc</div> </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include "caffe2/core/db.h"</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include "caffe2/core/init.h"</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include "caffe2/proto/caffe2.pb.h"</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include "caffe/proto/caffe.pb.h"</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include "caffe2/core/logging.h"</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> CAFFE2_DEFINE_string(input_db, <span class="stringliteral">""</span>, <span class="stringliteral">"The input db."</span>);</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> CAFFE2_DEFINE_string(input_db_type, <span class="stringliteral">""</span>, <span class="stringliteral">"The input db type."</span>);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> CAFFE2_DEFINE_string(output_db, <span class="stringliteral">""</span>, <span class="stringliteral">"The output db."</span>);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> CAFFE2_DEFINE_string(output_db_type, <span class="stringliteral">""</span>, <span class="stringliteral">"The output db type."</span>);</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> CAFFE2_DEFINE_int(batch_size, 1000, <span class="stringliteral">"The write batch size."</span>);</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="keyword">using</span> <a class="code" href="classcaffe2_1_1db_1_1_cursor.html">caffe2::db::Cursor</a>;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword">using</span> <a class="code" href="classcaffe2_1_1db_1_1_d_b.html">caffe2::db::DB</a>;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="keyword">using</span> <a class="code" href="classcaffe2_1_1db_1_1_transaction.html">caffe2::db::Transaction</a>;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keyword">using</span> caffe2::TensorProto;</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="keyword">using</span> caffe2::TensorProtos;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keywordtype">int</span> main(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>** argv) {</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <a class="code" href="namespacecaffe2.html#af70b04a01a1779ddd61f9ef1e0a141b7">caffe2::GlobalInit</a>(&argc, &argv);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> </div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  std::unique_ptr<DB> in_db(caffe2::db::CreateDB(</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  caffe2::FLAGS_input_db_type, caffe2::FLAGS_input_db, caffe2::db::READ));</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  std::unique_ptr<DB> out_db(caffe2::db::CreateDB(</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  caffe2::FLAGS_output_db_type, caffe2::FLAGS_output_db, caffe2::db::NEW));</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  std::unique_ptr<Cursor> cursor(in_db->NewCursor());</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  std::unique_ptr<Transaction> transaction(out_db->NewTransaction());</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordtype">int</span> count = 0;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">for</span> (; cursor->Valid(); cursor->Next()) {</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  caffe::Datum datum;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  CAFFE_ENFORCE(datum.ParseFromString(cursor->value()));</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  TensorProtos protos;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  TensorProto* data = protos.add_protos();</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  TensorProto* label = protos.add_protos();</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  label->set_data_type(TensorProto::INT32);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  label->add_dims(1);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  label->add_int32_data(datum.label());</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">if</span> (datum.encoded()) {</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="comment">// This is an encoded image. we will copy over the data directly.</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  data->set_data_type(TensorProto::STRING);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  data->add_dims(1);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  data->add_string_data(datum.data());</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="comment">// float data not supported right now.</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  CAFFE_ENFORCE_EQ(datum.float_data_size(), 0);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  std::vector<char> buffer_vec(datum.data().size());</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordtype">char</span>* buffer = buffer_vec.data();</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// swap order from CHW to HWC</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordtype">int</span> channels = datum.channels();</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordtype">int</span> size = datum.height() * datum.width();</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  CAFFE_ENFORCE_EQ(datum.data().size(), channels * size);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> c = 0; c < channels; ++c) {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keywordtype">char</span>* dst = buffer + c;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* src = datum.data().c_str() + c * size;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> n = 0; n < size; ++n) {</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  dst[n*channels] = src[n];</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  }</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  }</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  data->set_data_type(TensorProto::BYTE);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  data->add_dims(datum.height());</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  data->add_dims(datum.width());</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  data->add_dims(datum.channels());</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  data->set_byte_data(buffer, datum.data().size());</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  }</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  transaction->Put(cursor->key(), protos.SerializeAsString());</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordflow">if</span> (++count % caffe2::FLAGS_batch_size == 0) {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  transaction->Commit();</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  LOG(INFO) << <span class="stringliteral">"Converted "</span> << count << <span class="stringliteral">" items so far."</span>;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  }</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  }</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  LOG(INFO) << <span class="stringliteral">"A total of "</span> << count << <span class="stringliteral">" items processed."</span>;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> }</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="ttc" id="namespacecaffe2_html_af70b04a01a1779ddd61f9ef1e0a141b7"><div class="ttname"><a href="namespacecaffe2.html#af70b04a01a1779ddd61f9ef1e0a141b7">caffe2::GlobalInit</a></div><div class="ttdeci">bool GlobalInit(int *pargc, char ***pargv)</div><div class="ttdoc">Initialize the global environment of caffe2. </div><div class="ttdef"><b>Definition:</b> <a href="init_8cc_source.html#l00018">init.cc:18</a></div></div>
<div class="ttc" id="classcaffe2_1_1db_1_1_transaction_html"><div class="ttname"><a href="classcaffe2_1_1db_1_1_transaction.html">caffe2::db::Transaction</a></div><div class="ttdoc">An abstract class for the current database transaction while writing. </div><div class="ttdef"><b>Definition:</b> <a href="db_8h_source.html#l00061">db.h:61</a></div></div>
<div class="ttc" id="classcaffe2_1_1db_1_1_cursor_html"><div class="ttname"><a href="classcaffe2_1_1db_1_1_cursor.html">caffe2::db::Cursor</a></div><div class="ttdoc">An abstract class for the cursor of the database while reading. </div><div class="ttdef"><b>Definition:</b> <a href="db_8h_source.html#l00022">db.h:22</a></div></div>
<div class="ttc" id="classcaffe2_1_1db_1_1_d_b_html"><div class="ttname"><a href="classcaffe2_1_1db_1_1_d_b.html">caffe2::db::DB</a></div><div class="ttdoc">An abstract class for accessing a database of key-value pairs. </div><div class="ttdef"><b>Definition:</b> <a href="db_8h_source.html#l00080">db.h:80</a></div></div>
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