[GitHub] [incubator-mxnet] anirudhacharya commented on a change in pull request #14503: API to create RecordIO files

[GitBox <gi...@apache.org>]

anirudhacharya commented on a change in pull request #14503: API to create RecordIO files
URL: https://github.com/apache/incubator-mxnet/pull/14503#discussion_r268224481
 
 

 ##########
 File path: python/mxnet/io/io.py
 ##########
 @@ -966,6 +985,165 @@ def creator(*args, **kwargs):
     creator.__doc__ = doc_str
     return creator
 
+
+def _read_list(list_file, batch_size):
+    """
+    Helper function that reads the .lst file, binds it in
+    a generator and returns a batched version of the generator.
+    Parameters
+    ----------
+    list_file: input list file.
+    batch_size: batch size of the generator
+    Returns
+    -------
+    item iterator that contains information in .lst file
+    """
+    def get_generator():
+        with open(list_file) as fin:
+            while True:
+                line = fin.readline()
+                if not line:
+                    break
+                line = [i.strip() for i in line.strip().split('\t')]
+                line_len = len(line)
+                # check the data format of .lst file
+                if line_len < 3:
+                    logging.info("lst should have at least has three parts, "
+                                + "but only has {} parts for {}".format(line_len, line))
+                    continue
+                try:
+                    item = [int(line[0])] + [line[-1]] + [float(i) for i in line[1:-1]]
+                except Exception as e:
+                    logging.info('Parsing lst met error for {}, detail: {}'.format(line, e))
+                    continue
+                yield item
+    data_iter = iter(get_generator())
+    data_batch = list(itertools.islice(data_iter, batch_size))
+    while data_batch:
+        yield data_batch
+        data_batch = list(itertools.islice(data_iter, batch_size))
+
+def _read_worker(q_out, transforms, color, quality, encoding, data_record):
+    """
+    Helper function that will be run by the read workers
+    to fetch the image from the input queue apply
+    transformations and put it into output priority queue.
+    Parameters
+    ----------
+    args: object
+    q_out: queue
+    color: color
+    quality: quality
+    encoding: encoding
+    deq: image instance to work on.
+    """
+    i, item = data_record
+    fullpath = os.path.join(args.root, item[1])
+    try:
+        # construct the header of the record
+        if len(item) > 3:
+            header = recordio.IRHeader(0, item[2:], item[0], 0)
+        else:
+            header = recordio.IRHeader(0, item[2], item[0], 0)
+
+        img = cv2.imread(fullpath, args.color)
+        if img is None:
+            logging.info('imread read blank (None) image for file: %s' % fullpath)
+            return
+        img = transforms(img)
+        s = recordio.pack_img(header, img, quality=args.quality, img_fmt=args.encoding)
+        q_out.put((i, s, item))
+    except Exception as e:
+        logging.info('pack_img error on file: %s' % fullpath, e)
 
 Review comment:
   add different logging message for different kinds of exception

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