diff --git a/models/cv/classification/ixrt_common/config/RESNETV1D50_CONFIG b/models/cv/classification/ixrt_common/config/RESNETV1D50_CONFIG
index 0bf91b048fc29cee29714b613cff22cc5874d66c..2c87e1d70901fb26ca07fd4c96fe5c75d4e15df6 100644
--- a/models/cv/classification/ixrt_common/config/RESNETV1D50_CONFIG
+++ b/models/cv/classification/ixrt_common/config/RESNETV1D50_CONFIG
@@ -26,7 +26,7 @@ ORIGINE_MODEL=resnet_v1_d50.onnx
     # QUANT_SEED : 随机种子 保证量化结果可复现
     # QUANT_EXIST_ONNX : 如果有其他来源的量化模型则填写
 QUANT_OBSERVER=minmax
-QUANT_BATCHSIZE=1
+QUANT_BATCHSIZE=32
 QUANT_STEP=32
 QUANT_SEED=42
 DISABLE_QUANT_LIST=
diff --git a/models/cv/object_detection/retinaface/ixrt/inference.py b/models/cv/object_detection/retinaface/ixrt/inference.py
index 7c93103cf154e9fb2f46af9d685084ed357c89c6..3d99cb818846f27ab47f47f543c0a2f18e57d92f 100644
--- a/models/cv/object_detection/retinaface/ixrt/inference.py
+++ b/models/cv/object_detection/retinaface/ixrt/inference.py
@@ -83,6 +83,8 @@ def post_process(args, prior_data, locs, confs, landms, resizes, img_files, net_
         dets = np.concatenate((dets, landm), axis=1)
 
         # --------------------------------------------------------------------
+        if img_name.startswith("/"):
+            img_name = img_name[1:]
         save_name = os.path.join(args.save_folder, f"{img_name[:-4]}.txt")
         dirname = os.path.dirname(save_name)
         if not os.path.isdir(dirname):
diff --git a/models/cv/object_detection/yolov4/igie/README.md b/models/cv/object_detection/yolov4/igie/README.md
index 99dee0ffd8824adbfa3f56cc3ab0b9529e987295..506f8f669ce50e201757eb8ca24fcd75aae27c06 100644
--- a/models/cv/object_detection/yolov4/igie/README.md
+++ b/models/cv/object_detection/yolov4/igie/README.md
@@ -16,6 +16,7 @@ YOLOv4 employs a two-step process, involving regression for bounding box positio
 ### Prepare Resources
 
 Pretrained cfg: <https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4.cfg>
+
 Pretrained model: <https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v3_optimal/yolov4.weights>
 
 Dataset:
diff --git a/models/cv/object_detection/yolov4/ixrt/README.md b/models/cv/object_detection/yolov4/ixrt/README.md
index 60b73eb00a8d7d394bf9da9dfa3bd6bfbf211606..9cfb9f8be49b8fdea788084b36e4c350c25f5908 100644
--- a/models/cv/object_detection/yolov4/ixrt/README.md
+++ b/models/cv/object_detection/yolov4/ixrt/README.md
@@ -16,6 +16,7 @@ YOLOv4 employs a two-step process, involving regression for bounding box positio
 ### Prepare Resources
 
 Pretrained cfg: <https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4.cfg>
+
 Pretrained model: <https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v3_optimal/yolov4.weights>
 
 Dataset:
diff --git a/tests/model_info.json b/tests/model_info.json
index b13dcb19066e012d6f0e33e855ec23ae7bf44aa3..11d7dff9f164d1569d63fb8bc717e7b9507da601 100644
--- a/tests/model_info.json
+++ b/tests/model_info.json
@@ -2493,7 +2493,8 @@
             "download_url": "https://download.openmmlab.com/mmclassification/v0/resnet/resnetv1d50_b32x8_imagenet_20210531-db14775a.pth",
             "need_third_part": false,
             "precisions": [
-                "fp16"
+                "fp16",
+                "int8"
             ],
             "type": "inference",
             "hasDemo": false,