add image check

visualdl/logic/sdk.cc

@@ -119,7 +119,11 @@ void Image::SetSample(int index,
   for (int i = 0; i < data.size(); i++) {
     data_str[i] = data[i];
   }
-  entry.SetRaw(std::string(data_str.begin(), data_str.end()));
+  Uint8Image image(shape[2], shape[0] * shape[1]);
+  NormalizeImage(&image, &data[0], shape[0] * shape[1], shape[2]);
+  // entry.SetRaw(std::string(data_str.begin(), data_str.end()));
+  entry.SetRaw(
+      std::string(image.data(), image.data() + image.rows() * image.cols()));
 
   static_assert(
       !is_same_type<value_t, shape_t>::value,

visualdl/python/test_storage.py

@@ -42,7 +42,7 @@ class StorageTest(unittest.TestCase):
         for pass_ in xrange(num_passes):
             image_writer.start_sampling()
             for ins in xrange(num_samples):
-                index =  image_writer.is_sample_taken()
+                index = image_writer.is_sample_taken()
                 if index != -1:
                     data = np.random.random(shape) * 256
                     data = np.ndarray.flatten(data)
@@ -89,19 +89,14 @@ class StorageTest(unittest.TestCase):
         data = image_record.data()
         shape = image_record.shape()
 
-        PIL_image_shape = (shape[0]*shape[1], shape[2])
+        PIL_image_shape = (shape[0] * shape[1], shape[2])
         data = np.array(data, dtype='uint8').reshape(PIL_image_shape)
         print 'origin', origin_data.flatten()
         print 'data', data.flatten()
         image = Image.fromarray(data.reshape(shape))
 
-        self.assertTrue(np.equal(origin_data.reshape(PIL_image_shape), data).all())
-
-
-
-
-
-
+        self.assertTrue(
+            np.equal(origin_data.reshape(PIL_image_shape), data).all())
 
 
 if __name__ == '__main__':

visualdl/utils/image.h

@@ -13,7 +13,8 @@ using uint8_t = unsigned char;
  * 2: height*width, channel
  */
 template <typename T>
-using ImageDT = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>;
+using ImageDT =
+    Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>;
 using Uint8Image = ImageDT<uint8_t>;
 
 /*
@@ -21,10 +22,13 @@ using Uint8Image = ImageDT<uint8_t>;
  * depth: number of channels
  */
 static void NormalizeImage(Uint8Image* image,
-                           float* buffer,
+                           const float* buffer,
                            int hw,
                            int depth) {
-  Eigen::Map<Eigen::MatrixXf> values(buffer, depth, hw);
+  // Both image and buffer should be used in row major.
+  Eigen::Map<const Eigen::
+                 Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>
+      values(buffer, depth, hw);
 
   CHECK_EQ(image->size(), hw * depth);
   CHECK_EQ(image->row(0).size(), hw);
@@ -60,11 +64,12 @@ static void NormalizeImage(Uint8Image* image,
     float max_val = std::max(std::abs(image_min), image_max);
     scale = (max_val < kZeroThreshold ? 0.0f : 127.0f) / max_val;
   } else {
-    scale =
-        (image_max < image_max < kZeroThreshold ? 0.0f : 255.0f) / image_max;
+    scale = (image_max < kZeroThreshold ? 0.0f : 255.0f) / image_max;
     offset = 0.0f;
   }
 
+  LOG(INFO) << "scale " << scale;
+
   // Transform image, turning nonfinite values to bad_color
   for (int i = 0; i < depth; i++) {
     auto tmp = scale * values.row(i).array() + offset;