fix some bugs of unzip and reading val list

test=develop

paddle/fluid/inference/tests/api/full_ILSVRC2012_val_preprocess.py

@@ -71,10 +71,14 @@ def process_image(img_path, mode, color_jitter, rotate):
 
 
 def download_unzip():
+    int8_download = 'int8/download'
 
-    tmp_folder = 'int8/download'
+    target_name = 'data'
 
-    cache_folder = os.path.expanduser('~/.cache/' + tmp_folder)
+    cache_folder = os.path.expanduser('~/.cache/paddle/dataset/' +
+                                      int8_download)
+
+    target_folder = os.path.join(cache_folder, target_name)
 
     data_urls = []
     data_md5s = []
@@ -89,8 +93,9 @@ def download_unzip():
     data_md5s.append('1e9f15f64e015e58d6f9ec3210ed18b5')
 
     file_names = []
+
     for i in range(0, len(data_urls)):
-        download(data_urls[i], tmp_folder, data_md5s[i])
+        download(data_urls[i], cache_folder, data_md5s[i])
         file_names.append(data_urls[i].split('/')[-1])
 
     zip_path = os.path.join(cache_folder, 'full_imagenet_val.tar.gz')
@@ -101,16 +106,15 @@ def download_unzip():
             cat_command += ' ' + os.path.join(cache_folder, file_name)
         cat_command += ' > ' + zip_path
         os.system(cat_command)
+        print('Data is downloaded at {0}\n').format(zip_path)
 
-    if not os.path.exists(cache_folder):
-        cmd = 'mkdir {0} && tar xf {1} -C {0}'.format(cache_folder, zip_path)
-
-    cmd = 'rm -rf {3} && ln -s {1} {0}'.format("data", cache_folder, zip_path)
-
-    os.system(cmd)
-
-    data_dir = os.path.expanduser(cache_folder + 'data')
+    if not os.path.exists(target_folder):
+        cmd = 'mkdir {0} && tar xf {1} -C {0}'.format(target_folder, zip_path)
+        os.system(cmd)
+        print('Data is unzipped at {0}\n'.format(target_folder))
 
+    data_dir = os.path.join(target_folder, 'ILSVRC2012')
+    print('ILSVRC2012 full val set at {0}\n'.format(data_dir))
     return data_dir
 
 
@@ -121,32 +125,37 @@ def reader():
     with open(file_list) as flist:
         lines = [line.strip() for line in flist]
         num_images = len(lines)
-
-        with open(output_file, "w+b") as of:
-            #save num_images(int64_t) to file
-            of.seek(0)
-            num = np.array(int(num_images)).astype('int64')
-            of.write(num.tobytes())
-            for idx, line in enumerate(lines):
-                img_path, label = line.split()
-                img_path = os.path.join(data_dir, img_path)
-                if not os.path.exists(img_path):
-                    continue
-
-                #save image(float32) to file
-                img = process_image(
-                    img_path, 'val', color_jitter=False, rotate=False)
-                np_img = np.array(img)
-                of.seek(SIZE_INT64 + SIZE_FLOAT32 * DATA_DIM * DATA_DIM * 3 *
-                        idx)
-                of.write(np_img.astype('float32').tobytes())
-
-                #save label(int64_t) to file
-                label_int = (int)(label)
-                np_label = np.array(label_int)
-                of.seek(SIZE_INT64 + SIZE_FLOAT32 * DATA_DIM * DATA_DIM * 3 *
-                        num_images + idx * SIZE_INT64)
-                of.write(np_label.astype('int64').tobytes())
+        if not os.path.exists(output_file):
+            print(
+                'Preprocessing to binary file...<num_images><all images><all labels>...\n'
+            )
+            with open(output_file, "w+b") as of:
+                #save num_images(int64_t) to file
+                of.seek(0)
+                num = np.array(int(num_images)).astype('int64')
+                of.write(num.tobytes())
+                for idx, line in enumerate(lines):
+                    img_path, label = line.split()
+                    img_path = os.path.join(data_dir, img_path)
+                    if not os.path.exists(img_path):
+                        continue
+
+                    #save image(float32) to file
+                    img = process_image(
+                        img_path, 'val', color_jitter=False, rotate=False)
+                    np_img = np.array(img)
+                    of.seek(SIZE_INT64 + SIZE_FLOAT32 * DATA_DIM * DATA_DIM * 3
+                            * idx)
+                    of.write(np_img.astype('float32').tobytes())
+
+                    #save label(int64_t) to file
+                    label_int = (int)(label)
+                    np_label = np.array(label_int)
+                    of.seek(SIZE_INT64 + SIZE_FLOAT32 * DATA_DIM * DATA_DIM * 3
+                            * num_images + idx * SIZE_INT64)
+                    of.write(np_label.astype('int64').tobytes())
+
+        print('The preprocessed binary file path {}\n'.format(output_file))
 
 
 if __name__ == '__main__':