add thresoutput

deploy/configs/cls_demo/person/inference_person_cls.yaml

@@ -27,9 +27,10 @@ PreProcess:
     - ToCHWImage:
 
 PostProcess:
-  main_indicator: Topk
-  Topk:
-    topk: 5
-    class_id_map_file: "../ppcls/utils/cls_demo/person_label_list.txt"
+  main_indicator: ThreshOutput
+  ThreshOutput:
+    threshold: 0.9
+    label_0: invalid
+    label_1: valid
   SavePreLabel:
     save_dir: ./pre_label/

deploy/python/postprocess.py

@@ -53,6 +53,26 @@ class PostProcesser(object):
         return rtn
 
 
+class ThreshOutput(object):
+    def __init__(self, threshold, label_0="0", label_1="1"):
+        self.threshold = threshold
+        self.label_0 = label_0
+        self.label_1 = label_1
+
+    def __call__(self, x, file_names=None):
+        y = []
+        for idx, probs in enumerate(x):
+            score = probs[1]
+            if score < self.threshold:
+                result = {"class_ids": [0], "scores":  [1 - score], "label_names": [self.label_0]}
+            else:
+                result = {"class_ids": [1], "scores": [score], "label_names": [self.label_1]}
+            if file_names is not None:
+                result["file_name"] = file_names[idx]
+            y.append(result)
+        return y
+
+
 class Topk(object):
     def __init__(self, topk=1, class_id_map_file=None):
         assert isinstance(topk, (int, ))