From 0d16f6ec30f8e7be9c4a0f91776419c0a6540d99 Mon Sep 17 00:00:00 2001
From: "q.yao" <yaoqian@sensetime.com>
Date: Fri, 25 Nov 2022 17:31:44 +0800
Subject: [PATCH] fix pad to square (#1436)

* fix pad to square

* fix topk

* remove comment

* recovery topk
---
 .../codebase/mmdet/deploy/object_detection.py | 20 ++++++-------------
 1 file changed, 6 insertions(+), 14 deletions(-)

diff --git a/mmdeploy/codebase/mmdet/deploy/object_detection.py b/mmdeploy/codebase/mmdet/deploy/object_detection.py
index 786fdb1f3..fabf49546 100644
--- a/mmdeploy/codebase/mmdet/deploy/object_detection.py
+++ b/mmdeploy/codebase/mmdet/deploy/object_detection.py
@@ -7,7 +7,7 @@ import torch
 from mmcv.parallel import DataContainer
 from torch.utils.data import Dataset
 
-from mmdeploy.utils import Task, get_input_shape, is_dynamic_shape
+from mmdeploy.utils import Task, get_input_shape
 from ...base import BaseTask
 from .mmdetection import MMDET_TASK
 
@@ -44,7 +44,10 @@ def process_model_config(model_cfg: mmcv.Config,
             if trans_type == 'Resize' and len(input_shape) != 1:
                 trans['keep_ratio'] = False
             elif trans_type == 'Pad':
-                if 'size_divisor' in trans:
+                if trans.get('pad_to_square', False):
+                    # pad_to_square is mutually exclusive with size and divisor
+                    pass
+                elif 'size_divisor' in trans:
                     trans['size_divisor'] = 1
                 else:
                     trans['size'] = tuple(input_shape)
@@ -122,22 +125,11 @@ class ObjectDetection(BaseTask):
         from mmdet.datasets.pipelines import Compose
         if isinstance(imgs, (str, np.ndarray)):
             imgs = [imgs]
-        dynamic_flag = is_dynamic_shape(self.deploy_cfg)
         model_cfg = self.model_cfg
         if pipeline_updater is not None:
             model_cfg = pipeline_updater(self.deploy_cfg, model_cfg)
         cfg = process_model_config(model_cfg, imgs, input_shape)
-        # Drop pad_to_square when static shape. Because static shape should
-        # ensure the shape before input image.
-        if not dynamic_flag:
-            transform = cfg.data.test.pipeline[1]
-            if 'transforms' in transform:
-                transform_list = transform['transforms']
-                for i, step in enumerate(transform_list):
-                    if step['type'] == 'Pad' and 'pad_to_square' in step \
-                       and step['pad_to_square']:
-                        transform_list.pop(i)
-                        break
+
         test_pipeline = Compose(cfg.data.test.pipeline)
         data_list = []
         for img in imgs: