fix bug in ai/video z4

backend_refactor/service/ai/video/inner_analyze.py

@@ -180,8 +180,6 @@ def analyse_npy_side_shendun(data):
 
 def analyse_npy_side_jump(data):
     result = {}
-    logging.debug("calculate angle")
-    logging.debug(data)
     if len(data) == 0:
         # logging.warning("Data len is not 25, skipping.")
         return False

backend_refactor/service/ai/video/video_score/pingban.py

@@ -1,3 +1,7 @@
+import logging
+import sys
+
+
 def cal_ratio(measured_angle, max_angle):
     num1 = float(measured_angle)
     num2 = float(max_angle)
@@ -44,6 +48,8 @@ def cal_second_score(list):
 
 #
 def cal_pingban(result):
+    logging.debug(result)
+    sys.stdout.write(result)
     result_ig = result
     re = {}
     # clean the data

backend_refactor/service/video_analyzer.py

@@ -117,7 +117,7 @@ class BaseVideoAnalyzer:
 class JumpVideoAnalyzer(BaseVideoAnalyzer):
     def _do_analyze(self):
         self.results = {k: analyse_npy_side_jump(v) for k, v in self.results.items()}
-        self.results = {k: v for k, v in self.results.items() if v != False}
+        self.results = {k: v for k, v in self.results.items() if v is not False}
         raw = cal_jump(self.results)[1]
         return classify_jump(raw)
 
@@ -125,8 +125,7 @@ class JumpVideoAnalyzer(BaseVideoAnalyzer):
 class PingbanVideoAnalyzer(BaseVideoAnalyzer):
     def _do_analyze(self):
         self.results = {k: analyse_npy_side_jump(v) for k, v in self.results.items()}
-        self.results = {k: v for k, v in self.results.items() if v != False}
-        logging.debug(self.results)
+        self.results = {k: v for k, v in self.results.items() if v is not False}
         raw = cal_pingban(self.results)[1]
         return classify_pingban(raw)
 
@@ -134,7 +133,7 @@ class PingbanVideoAnalyzer(BaseVideoAnalyzer):
 class JuanfuVideoAnalyzer(BaseVideoAnalyzer):
     def _do_analyze(self):
         self.results = {k: analyse_npy_side_juanfu(v) for k, v in self.results.items()}
-        self.results = {k: v for k, v in self.results.items() if v != False}
+        self.results = {k: v for k, v in self.results.items() if v is not False}
         raw = ignore_data_juanfu(self.results)[1]
         return classify_juanfu(raw)
 
@@ -142,7 +141,7 @@ class JuanfuVideoAnalyzer(BaseVideoAnalyzer):
 class ShendunVideoAnalyzer(BaseVideoAnalyzer):
     def _do_analyze(self):
         self.results = {k: analyse_npy_side_shendun(v) for k, v in self.results.items()}
-        self.results = {k: v for k, v in self.results.items() if v != False}
+        self.results = {k: v for k, v in self.results.items() if v is not False}
         raw = ignore_data_shendun(self.results)[1]
         return classify_shendun(raw)
 
@@ -150,7 +149,7 @@ class ShendunVideoAnalyzer(BaseVideoAnalyzer):
 class GaotaituiVideoAnalyzer(BaseVideoAnalyzer):
     def _do_analyze(self):
         self.results = {k: analyse_npy_side_gaotaitui(v) for k, v in self.results.items()}
-        self.results = {k: v for k, v in self.results.items() if v != False}
+        self.results = {k: v for k, v in self.results.items() if v is not False}
         raw = ignore_data_gaotaitui(self.results)[1]
         return classify_gaotaitui(raw)
 
@@ -158,7 +157,7 @@ class GaotaituiVideoAnalyzer(BaseVideoAnalyzer):
 class TurnaroundVideoAnalyzer(BaseVideoAnalyzer):
     def _do_analyze(self):
         self.results = {k: analyse_npy_side_jump(v) for k, v in self.results.items()}
-        self.results = {k: v for k, v in self.results.items() if v != False}
+        self.results = {k: v for k, v in self.results.items() if v is not False}
         raw = cal_turnaround(self.results)[1]
         return classify_turnaround(raw)
 
@@ -166,7 +165,7 @@ class TurnaroundVideoAnalyzer(BaseVideoAnalyzer):
 class TennisthrowVideoAnalyzer(BaseVideoAnalyzer):
     def _do_analyze(self):
         self.results = {k: analyse_npy_side_jump(v) for k, v in self.results.items()}
-        self.results = {k: v for k, v in self.results.items() if v != False}
+        self.results = {k: v for k, v in self.results.items() if v is not False}
         raw = cal_tennisthrow(self.results)[1]
         return classify_tennisthrow(raw)