support visualdl in preprocess data (#1828)

* support visualdl in preprocess data

* support most preprocess op

ppdet/data/transform/operators.py

@@ -33,9 +33,10 @@ import random
 import math
 import numpy as np
 import os
+import six
 
 import cv2
-from PIL import Image, ImageEnhance, ImageDraw
+from PIL import Image, ImageEnhance, ImageDraw, ImageOps
 
 from ppdet.core.workspace import serializable
 from ppdet.modeling.ops import AnchorGrid
@@ -2535,22 +2536,65 @@ class DebugVisibleImage(BaseOperator):
     (Currently only supported when not cropping and flipping image.)
     """
 
-    def __init__(self, output_dir='output/debug', is_normalized=False):
+    def __init__(self,
+                 output_dir='output/debug',
+                 use_vdl=False,
+                 is_normalized=False):
         super(DebugVisibleImage, self).__init__()
         self.is_normalized = is_normalized
         self.output_dir = output_dir
+        self.use_vdl = use_vdl
         if not os.path.isdir(output_dir):
             os.makedirs(output_dir)
         if not isinstance(self.is_normalized, bool):
             raise TypeError("{}: input type is invalid.".format(self))
+        if self.use_vdl:
+            assert six.PY3, "VisualDL requires Python >= 3.5"
+            from visualdl import LogWriter
+            self.vdl_writer = LogWriter(self.output_dir)
 
     def __call__(self, sample, context=None):
-        image = Image.open(sample['im_file']).convert('RGB')
         out_file_name = sample['im_file'].split('/')[-1]
+        if self.use_vdl:
+            origin_image = Image.open(sample['im_file']).convert('RGB')
+            origin_image = ImageOps.exif_transpose(origin_image)
+            image_np = np.array(origin_image)
+            self.vdl_writer.add_image("original/{}".format(out_file_name),
+                                      image_np, 0)
+
+        if not isinstance(sample['image'], np.ndarray):
+            raise TypeError("{}: sample[image] type is not numpy.".format(self))
+        image = Image.fromarray(np.uint8(sample['image']))
+
         width = sample['w']
         height = sample['h']
         gt_bbox = sample['gt_bbox']
         gt_class = sample['gt_class']
+
+        if 'gt_poly' in sample.keys():
+            poly_to_mask = Poly2Mask()
+            sample = poly_to_mask(sample)
+
+        if 'gt_segm' in sample.keys():
+            import pycocotools.mask as mask_util
+            from ppdet.utils.colormap import colormap
+            image_np = np.array(image).astype('float32')
+            mask_color_id = 0
+            w_ratio = .4
+            alpha = 0.7
+            color_list = colormap(rgb=True)
+            gt_segm = sample['gt_segm']
+            for mask in gt_segm:
+                color_mask = color_list[mask_color_id % len(color_list), 0:3]
+                mask_color_id += 1
+                for c in range(3):
+                    color_mask[c] = color_mask[c] * (1 - w_ratio
+                                                     ) + w_ratio * 255
+                idx = np.nonzero(mask)
+                image_np[idx[0], idx[1], :] *= 1.0 - alpha
+                image_np[idx[0], idx[1], :] += alpha * color_mask
+            image = Image.fromarray(np.uint8(image_np))
+
         draw = ImageDraw.Draw(image)
         for i in range(gt_bbox.shape[0]):
             if self.is_normalized:
@@ -2566,7 +2610,7 @@ class DebugVisibleImage(BaseOperator):
                 width=2,
                 fill='green')
             # draw label
-            text = str(gt_class[i][0])
+            text = 'id' + str(gt_class[i][0])
             tw, th = draw.textsize(text)
             draw.rectangle(
                 [(xmin + 1, ymin - th), (xmin + tw + 1, ymin)], fill='green')
@@ -2583,12 +2627,17 @@ class DebugVisibleImage(BaseOperator):
             for i in range(gt_keypoint.shape[0]):
                 keypoint = gt_keypoint[i]
                 for j in range(int(keypoint.shape[0] / 2)):
-                    x1 = round(keypoint[2 * j]).astype(np.int32)
-                    y1 = round(keypoint[2 * j + 1]).astype(np.int32)
+                    x1 = round(keypoint[2 * j])
+                    y1 = round(keypoint[2 * j + 1])
                     draw.ellipse(
                         (x1, y1, x1 + 5, y1 + 5), fill='green', outline='green')
         save_path = os.path.join(self.output_dir, out_file_name)
-        image.save(save_path, quality=95)
+        if self.use_vdl:
+            preprocess_image_np = np.array(image)
+            self.vdl_writer.add_image("preprocess/{}".format(out_file_name),
+                                      preprocess_image_np, 0)
+        else:
+            image.save(save_path, quality=95)
         return sample