add wget and unzip part and change data_dir

test=develop

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

@@ -21,6 +21,7 @@ import functools
 import contextlib
 from PIL import Image, ImageEnhance
 import math
+from paddle.dataset.common import download
 
 random.seed(0)
 np.random.seed(0)
@@ -30,8 +31,6 @@ DATA_DIM = 224
 SIZE_FLOAT32 = 4
 SIZE_INT64 = 8
 
-DATA_DIR = './data/ILSVRC2012/data.bin'
-
 img_mean = np.array([0.485, 0.456, 0.406]).reshape((3, 1, 1))
 img_std = np.array([0.229, 0.224, 0.225]).reshape((3, 1, 1))
 
@@ -71,15 +70,60 @@ def process_image(img_path, mode, color_jitter, rotate):
     return img
 
 
+def download_unzip():
+
+    tmp_folder = 'int8/download'
+
+    cache_folder = os.path.expanduser('~/.cache/' + tmp_folder)
+
+    data_urls = []
+    data_md5s = []
+
+    data_urls.append(
+        'https://paddle-inference-dist.bj.bcebos.com/int8/ILSVRC2012_img_val.tar.gz.partaa'
+    )
+    data_md5s.append('60f6525b0e1d127f345641d75d41f0a8')
+    data_urls.append(
+        'https://paddle-inference-dist.bj.bcebos.com/int8/ILSVRC2012_img_val.tar.gz.partab'
+    )
+    data_md5s.append('1e9f15f64e015e58d6f9ec3210ed18b5')
+
+    file_names = []
+    for i in range(0, len(data_urls)):
+        download(data_urls[i], tmp_folder, data_md5s[i])
+        file_names.append(data_urls[i].split('/')[-1])
+
+    zip_path = os.path.join(cache_folder, 'full_imagenet_val.tar.gz')
+
+    if not os.path.exists(zip_path):
+        cat_command = 'cat'
+        for file_name in file_names:
+            cat_command += ' ' + os.path.join(cache_folder, file_name)
+        cat_command += ' > ' + zip_path
+        os.system(cat_command)
+
+    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')
+
+    return data_dir
+
+
 def reader():
-    data_dir = DATA_DIR
+    data_dir = download_unzip()
     file_list = os.path.join(data_dir, 'val_list.txt')
-    bin_file = os.path.join(data_dir, 'data.bin')
+    output_file = os.path.join(data_dir, 'int8_full_val.bin')
     with open(file_list) as flist:
         lines = [line.strip() for line in flist]
         num_images = len(lines)
 
-        with open(bin_file, "w+b") as of:
+        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())