test

Author: vishnubanna

yolo/dataloaders/yolo_input_test.py

@@ -31,30 +31,32 @@ def test_yolo_input_task():
             # boxes = ['(10, 14)', '(23, 27)', '(37, 58)', '(81, 82)', '(135, 169)', '(344, 319)'],
             # boxes = ["(10, 13)", "(16, 30)", "(33, 23)","(30, 61)", "(62, 45)", "(59, 119)","(116, 90)", "(156, 198)", "(373, 326)"],
             # boxes =  ['(10, 14)', '(23, 27)', '(37, 58)', '(81, 82)'], #, '(135, 169)'])
+            boxes=[
+                '(12, 16)', '(19, 36)', '(40, 28)', '(36, 75)', '(76, 55)',
+                '(72, 146)', '(142, 110)', '(192, 243)', '(459, 401)'
+            ],
             # boxes=[
-            #     '(12, 16)', '(19, 36)', '(40, 28)', '(36, 75)', '(76, 55)',
-            #     '(72, 146)', '(142, 110)', '(192, 243)', '(459, 401)'
+            #     '[15.0, 20.0]', '[23.0, 45.0]', '[50.0, 35.0]', '[45.0, 93.0]',
+            #     '[95.0, 68.0]', '[90.0, 182.0]', '[177.0, 137.0]',
+            #     '[240.0, 303.0]', '[573.0, 501.0]'
             # ],
-            boxes = ['[15.0, 20.0]', 
-             '[23.0, 45.0]', 
-             '[50.0, 35.0]', 
-             '[45.0, 93.0]', 
-             '[95.0, 68.0]', 
-             '[90.0, 182.0]', 
-             '[177.0, 137.0]', 
-             '[240.0, 303.0]', 
-             '[573.0, 501.0]'],
             # boxes = None,
             filter=yolocfg.YoloLossLayer(nms_type="greedy")))
     task = yolo.YoloTask(config)
 
     # loading both causes issues, but oen at a time is not issue, why?
+    # config.train_data.global_batch_size = 64
+    # config.validation_data.global_batch_size = 64
     config.train_data.dtype = 'float32'
     config.validation_data.dtype = 'float32'
-    config.train_data.tfds_name = 'coco'
-    config.validation_data.tfds_name = 'coco'
-    config.train_data.tfds_split = 'train'
-    config.validation_data.tfds_split = 'validation'
+    # config.train_data.tfds_name = 'coco'
+    # config.validation_data.tfds_name = 'coco'
+    # config.train_data.tfds_split = 'train'
+    # config.validation_data.tfds_split = 'validation'
+    # config.train_data.tfds_data_dir = '/media/vbanna/DATA_SHARE/tfds'
+    # config.validation_data.tfds_data_dir = '/media/vbanna/DATA_SHARE/tfds'
+    config.train_data.input_path = '/media/vbanna/DATA_SHARE/CV/datasets/COCO_raw/records/train*'
+    config.validation_data.input_path = '/media/vbanna/DATA_SHARE/CV/datasets/COCO_raw/records/val*'
     train_data = task.build_inputs(config.train_data)
     test_data = task.build_inputs(config.validation_data)
   return train_data, test_data
@@ -107,7 +109,7 @@ def test_yolo_pipeline(is_training=True):
   print(dataset, dsp)
   # shind = 3
   dip = 0
-  drawer = utils.DrawBoxes(labels=coco.get_coco_names(), thickness=2)
+  drawer = utils.DrawBoxes(labels=coco.get_coco_names(path="/home/vbanna/Research/TensorFlowModels/yolo/dataloaders/dataset_specs/coco-91.names"), thickness=2, classes=91)
   # dfilter = detection_generator.YoloFilter()
   ltime = time.time()
 
@@ -166,28 +168,28 @@ def test_yolo_pipeline(is_training=True):
 
 def time_pipeline():
   dataset, dsp = test_yolo_input_task()
-  dataset = dataset.take(100000)
-  print(dataset, dataset.cardinality())
+  # dataset = dataset.take(100000)
+  # print(dataset, dataset.cardinality())
   times = []
   ltime = time.time()
   for l, (i, j) in enumerate(dataset):
     ftime = time.time()
     # print(tf.reduce_min(i))
     # print(l , ftime - ltime, end = ", ")
 
-    gt = j['true_conf']
-    inds = j['inds']
-    
-    with tf.device('CPU:0'):
-      test = tf.gather_nd(gt['3'], inds['3'], batch_dims=1)
-      test = tf.gather_nd(gt['4'], inds['4'], batch_dims=1)
-      test = tf.gather_nd(gt['5'], inds['5'], batch_dims=1)
-      tf.print(test)
+    # gt = j['true_conf']
+    # inds = j['inds']
+
+    # with tf.device('CPU:0'):
+    #   test = tf.gather_nd(gt['3'], inds['3'], batch_dims=1)
+    #   test = tf.gather_nd(gt['4'], inds['4'], batch_dims=1)
+    #   test = tf.gather_nd(gt['5'], inds['5'], batch_dims=1)
+      # tf.print(test)
 
     times.append(ftime - ltime)
     ltime = time.time()
     print(times[-1], l)
-    if l >= 80000:
+    if l >= 100:
       break
 
   plt.plot(times)