Add the APIs,scripts and models to support DCGAN.

data/Celeb-A/celebA.txt

@@ -0,0 +1,10 @@
+/Celeb-A_Cropped/000001.jpg 1
+/Celeb-A_Cropped/000002.jpg 1
+/Celeb-A_Cropped/000003.jpg 1
+/Celeb-A_Cropped/000004.jpg 1
+/Celeb-A_Cropped/000005.jpg 1
+/Celeb-A_Cropped/000006.jpg 1
+/Celeb-A_Cropped/000007.jpg 1
+/Celeb-A_Cropped/000008.jpg 1
+/Celeb-A_Cropped/000009.jpg 1
+/Celeb-A_Cropped/000010.jpg 1

data/Celeb-A/crop_celebA.py

@@ -0,0 +1,59 @@
+from PIL import Image
+import os
+import sys
+
+print ""
+print "Prepare Celeb-A Dataset! (1. Crop the images. 2. Generate a train list file.)"
+print ""
+print "-------------------------------------------------------------------------------"
+
+current_path = os.getcwd()
+celebA_path = ""
+celebA_cropped_path = ""
+print "The current path containing this python file is: " + current_path
+if len(sys.argv) == 1:
+    print "Please give the path of original Celeb-A dataset!"
+    exit(0)
+elif len(sys.argv) > 1:
+    print "The path of original Celeb-A dataset is: " + str(sys.argv[1])
+    celebA_path = sys.argv[1]
+    celebA_cropped_path = os.path.dirname(celebA_path) + os.sep + "Cropped"     #To avoid crop the generated images again if this parameter is not provided
+    if len(sys.argv) > 2:
+        print "The path of cropped Celeb-A dataset will be: " + str(sys.argv[2])
+        celebA_cropped_path = sys.argv[2]
+    else:
+        print "The path of cropped Celeb-A dataset will be defult, set as: " + celebA_cropped_path
+
+if os.path.exists(celebA_cropped_path):
+    print "The path of cropped Celeb-A dataset exists."
+else:
+    print "The path of cropped Celeb-A dataset doesn't exist! I will create it now!"
+    os.makedirs(celebA_cropped_path)
+print "-------------------------------------------------------------------------------"
+
+training_list_file = os.path.join(celebA_cropped_path, "celebA.txt")
+list_file = open(training_list_file, 'w')
+total_image_num = 0
+x1, y1 = 30, 40
+cropped_box = (x1, y1, x1 + 138, y1 + 138)
+
+for parent,dirnames,filenames in os.walk(celebA_path):
+    for filename in filenames:
+        if filename.endswith(".jpg"):
+            total_image_num += 1
+            #print "parent is:" + parent
+            #print "filename is:" + filename
+            image_path_and_name = os.path.join(parent,filename)
+            print "the full name of the file is: " + image_path_and_name
+            input_image = Image.open(image_path_and_name)
+            #input_image.show()
+            cropped_image = input_image.crop(cropped_box)
+            #cropped_image.show()
+            scaled_cropped_image = cropped_image.resize((64, 64))
+            #scaled_cropped_image.show()
+            save_result_image_path_and_name = os.path.join(celebA_cropped_path,filename)
+            scaled_cropped_image.save(save_result_image_path_and_name, 'jpeg')
+            list_file.writelines(save_result_image_path_and_name)
+            list_file.writelines(" 1" + "\n")   #Must add label to list file
+print "There are " + str(total_image_num) + " images are finished with cropping and scaling operations!"
+list_file.close()

include/caffe/net.hpp

@@ -326,6 +326,9 @@ class Net {
   /// @brief return whether NetState state meets NetStateRule rule
   static bool StateMeetsRule(const NetState& state, const NetStateRule& rule,
       const string& layer_name);
+  inline const map<string,int>& blob_names_index() const {
+    return blob_names_index_;
+  }
 
  protected:
   // Helpers for Init.

include/caffe/solver.hpp

@@ -113,6 +113,7 @@ class Solver {
   }
   int iter() { return iter_; }
   void set_iter(int value) { iter_ = value; }
+  void increment_iter() { iter_++; }
 
   // Invoked at specific points during an iteration
   class Callback {

models/intel_optimized_models/dcgan/data.prototxt

@@ -0,0 +1,17 @@
+
+layer {
+  name: "data"
+  type: "ImageData"
+  top: "data"
+  top: "label"
+  transform_param {
+    mirror: true
+    mean_value: 104
+    mean_value: 117
+    mean_value: 123
+  }
+  image_data_param {
+    source: "data/Celeb-A/celebA.txt"
+    batch_size: 64
+  }
+}