!18757 SE-net 310infer delete label file

Merge pull request !18757 from chenweitao_295/SE-net_amend

model_zoo/research/cv/SE-Net/README.md

@@ -221,10 +221,9 @@ Before performing inference, the mindir file must be exported by `export.py` scr
 
 ```shell
 # Ascend310 inference
-bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [LABEL_FILE] [DVPP] [DEVICE_ID]
+bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DVPP] [DEVICE_ID]
 ```
 
-- `LABEL_FILE` label.txt path. Write a py script to sort the category under the dataset, map the file names under the categories and category sort values,Such as[file name : sort value], and write the mapping results to the labe.txt file.
 - `DVPP` is mandatory, and must choose from ["DVPP", "CPU"], it's case-insensitive. SE-net only support CPU mode.
 - `DEVICE_ID` is optional, default value is 0.
 

model_zoo/research/cv/SE-Net/postprocess.py

@@ -19,7 +19,7 @@ import numpy as np
 
 parser = argparse.ArgumentParser(description='SE_net calcul acc')
 parser.add_argument("--result_path", type=str, required=True, default='', help="result file path")
-parser.add_argument("--label_file", type=str, required=True, default='', help="label file")
+parser.add_argument("--data_path", type=str, required=True, default='', help="data path")
 args = parser.parse_args()
 
 
@@ -31,20 +31,20 @@ def get_top5_acc(top_arg, gt_class):
     return sub_count
 
 
-def read_label(label_file):
-    with open(label_file, 'r') as f:
-        lines = f.readlines()
-    img_dict = {}
-    for line in lines:
-        img_id = line.split(':')[0]
-        label = line.split(':')[1]
-        img_dict[img_id] = label
-    return img_dict
+def get_label(data_path):
+    img_label = {}
+    dirs = os.listdir(data_path)
+    dirs = sorted(dirs)
+    for class_num, dir_ in enumerate(dirs):
+        files = os.listdir(os.path.join(data_path, dir_))
+        for file in files:
+            img_label[file.split('.')[0]] = class_num
+    return img_label
 
 
-def cal_acc_imagenet(result_path, label_file):
+def cal_acc_imagenet(result_path, data_path):
     """ calcul acc """
-    img_label = read_label(label_file)
+    img_label = get_label(data_path)
     img_tot = 0
     top1_correct = 0
     top5_correct = 0
@@ -70,4 +70,4 @@ def cal_acc_imagenet(result_path, label_file):
 
 
 if __name__ == '__main__':
-    cal_acc_imagenet(args.result_path, args.label_file)
+    cal_acc_imagenet(args.result_path, args.data_path)

model_zoo/research/cv/SE-Net/scripts/run_infer_310.sh

@@ -14,8 +14,8 @@
 # limitations under the License.
 # ============================================================================
 
-if [[ $# -lt 4 || $# -gt 5 ]]; then
-    echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [LABEL_FILE] [DVPP] [DEVICE_ID]
+if [[ $# -lt 3 || $# -gt 4 ]]; then
+    echo "Usage: bash run_infer_310.sh [MINDIR_PATH] [DATA_PATH] [DVPP] [DEVICE_ID]
     DVPP is mandatory, and must choose from [DVPP|CPU], it's case-insensitive,the net only support CPU mode.
     DEVICE_ID is optional, it can be set by environment variable device_id, otherwise the value is zero"
 exit 1
@@ -30,17 +30,15 @@ get_real_path(){
 }
 model=$(get_real_path $1)
 data_path=$(get_real_path $2)
-label_file=$(get_real_path $3)
-DVPP=${4^^}
+DVPP=${3^^}
 
 device_id=0
-if [ $# == 5 ]; then
-    device_id=$5
+if [ $# == 4 ]; then
+    device_id=$4
 fi
 
 echo "mindir name: "$model
 echo "dataset path: "$data_path
-echo "label file: "$label_file
 echo "image process mode: "$DVPP
 echo "device id: "$device_id
 
@@ -87,7 +85,7 @@ function infer()
 
 function cal_acc()
 {
-    python3.7 ../postprocess.py --label_file=$label_file --result_path=./result_Files &> acc.log &
+    python3.7 ../postprocess.py --data_path=$data_path --result_path=./result_Files &> acc.log &
 }
 
 compile_app