From c8b46e6eb66132a30648fe99f047899fd3ef3fe3 Mon Sep 17 00:00:00 2001
From: jonyguo <guozhijian@huawei.com>
Date: Mon, 20 Jun 2022 10:28:05 +0800
Subject: [PATCH] fix: retinaface_resnet50 probability failure
---
official/cv/retinaface_resnet50/src/config.py | 2 +-
.../cv/retinaface_resnet50/src/dataset.py | 25 ++++++++++++++++---
2 files changed, 22 insertions(+), 5 deletions(-)
diff --git a/official/cv/retinaface_resnet50/src/config.py b/official/cv/retinaface_resnet50/src/config.py
index 02553fc8e..473124ccf 100644
--- a/official/cv/retinaface_resnet50/src/config.py
+++ b/official/cv/retinaface_resnet50/src/config.py
@@ -20,7 +20,7 @@ cfg_res50 = {
'class_weight': 1.0,
'landm_weight': 1.0,
'batch_size': 8,
- 'num_workers': 8,
+ 'num_workers': 4,
'num_anchor': 29126,
'ngpu': 4,
'image_size': 840,
diff --git a/official/cv/retinaface_resnet50/src/dataset.py b/official/cv/retinaface_resnet50/src/dataset.py
index 18a3126b4..7a108e588 100644
--- a/official/cv/retinaface_resnet50/src/dataset.py
+++ b/official/cv/retinaface_resnet50/src/dataset.py
@@ -135,17 +135,34 @@ def create_dataset(data_dir, cfg, batch_size=32, repeat_num=1, shuffle=True, mul
aug = preproc(cfg['image_size'])
encode = bbox_encode(cfg)
- def union_data(image, annot):
+ def read_data_from_dataset(image, annot):
i, a = read_dataset(image, annot)
- i, a = aug(i, a)
- out = encode(i, a)
+ return i, a
+ def augmentation(image, annot):
+ i, a = aug(image, annot)
+ return i, a
+
+ def encode_data(image, annot):
+ out = encode(image, annot)
return out
+ de_dataset = de_dataset.map(input_columns=["image", "annotation"],
+ output_columns=["image", "annotation"],
+ column_order=["image", "annotation"],
+ operations=read_data_from_dataset,
+ python_multiprocessing=multiprocessing,
+ num_parallel_workers=num_worker)
+ de_dataset = de_dataset.map(input_columns=["image", "annotation"],
+ output_columns=["image", "annotation"],
+ column_order=["image", "annotation"],
+ operations=augmentation,
+ python_multiprocessing=multiprocessing,
+ num_parallel_workers=num_worker)
de_dataset = de_dataset.map(input_columns=["image", "annotation"],
output_columns=["image", "truths", "conf", "landm"],
column_order=["image", "truths", "conf", "landm"],
- operations=union_data,
+ operations=encode_data,
python_multiprocessing=multiprocessing,
num_parallel_workers=num_worker)
--
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