added doc and kap.py

.gitignore

@@ -10,3 +10,4 @@ __pycache__/
 *.mp4
 
 *.weights
+*.m4v

Application/Classifiers/Classifier.py

@@ -38,6 +38,8 @@ class Classifier(ClassifierInterface):
         for cnts in data:
             for cnt in cnts:
                 if cnt.any():
+                    cv2.imshow("changes x", cnt)
+                    cv2.waitKey(10) & 0XFF
                     cnt= imutils.resize(cnt, width=320)
                     x = self.detect(cnt)
 

Application/Config.py

@@ -1,7 +1,7 @@
 
 class Config:
     c = {
-        "min_area" : 500,
+        "min_area" : 100,
         "max_area" : 40000,
         "threashold" : 5,
         "resizeWidth" : 512,
@@ -12,7 +12,7 @@ class Config:
         "tolerance": 20,
         "maxLength": None,
         "ttolerance": 60,
-        "videoBufferLength": 16,
+        "videoBufferLength": 500,
         "noiseThreashold": 0.3,
         "noiseSensitivity": 3/4,
         "LayersPerContour": 5,

Application/LayerFactory.py

@@ -25,7 +25,7 @@ class LayerFactory:
     def extractLayers(self, data = None):
         '''Bundle given contours together into Layer Objects'''
         if self.data is None:
-            if data is None:
+            if data is None or len(data) == 0 :
                 print("LayerFactory data was none")
                 return None
             else:

Application/LayerManager.py

@@ -25,6 +25,7 @@ class LayerManager:
 
 
     def cleanLayers(self):
+        print("'Cleaning' Layers")
         self.freeMin()
         self.sortLayers()            
         self.cleanLayers2()
@@ -69,9 +70,10 @@ class LayerManager:
 
     def tagLayers(self):
         '''Use classifieres the tag all Layers, by reading the contour content from the original video, then applying the classifier'''
+        print("Tagging Layers")
         exporter = Exporter(self.config)
         start = time.time()
-        for i, layer in enumerate(self.layers):
+        for i, layer in enumerate(self.layers[20:]):
             print(f"{round(i/len(self.layers)*100,2)} {round((time.time() - start), 2)}")
             start = time.time()
             if len(layer.bounds[0]) == 0:

generate test footage/kap.py

@@ -0,0 +1,34 @@
+#python
+import cv2
+import imageio
+import time
+writer = imageio.get_writer("./x23.mp4", fps=20)
+        
+url = "http://50.227.41.1/mjpg/video.mjpg"
+i = 0
+cap = cv2.VideoCapture(url)
+while True :
+    try:
+        if i < 10:
+            i+=1
+            continue
+        
+        
+        result, frame = cap.read()
+        
+        if result == False: 
+            print("Error in cap.read()") # this is for preventing a breaking error 
+            # break;
+            time.sleep(1) 
+            continue
+        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        writer.append_data(frame)
+        i+=1
+
+        if i > 20*60*60:
+            break
+    except Exception as e:
+
+        cap.release()
+        cv2.destroyAllWindows()
+        writer.close()

main.py

@@ -14,9 +14,9 @@ def main():
     start = time.time()
     config = Config()
 
-    config["inputPath"] = os.path.join(os.path.dirname(__file__), "generate test footage/3.mp4")
+    config["inputPath"] = os.path.join(os.path.dirname(__file__), "generate test footage/Merica-1.m4v")
-    config["importPath"] = os.path.join(os.path.dirname(__file__), "output/short.txt")
+    #config["importPath"] = os.path.join(os.path.dirname(__file__), "output/short.txt")
-    config["outputPath"]  = os.path.join(os.path.dirname(__file__), "output/short.mp4")
+    config["outputPath"]  = os.path.join(os.path.dirname(__file__), "output/shor.mp4")
 
     vr = VideoReader(config)
     config["w"], config["h"] = vr.getWH()
@@ -34,7 +34,7 @@ def main():
     layerManager = LayerManager(config, layers)
     layerManager.cleanLayers()
 
-    layerManager.tagLayers()
+    #layerManager.tagLayers()
     layers = layerManager.layers
     exporter = Exporter(config)
     exporter.export(layers, raw=False)