added json config support

Application/Config.py

@@ -1,8 +1,12 @@
+import json
+import os
+
+
 class Config:
     c = {
         "min_area": 300,
         "max_area": 900000,
-        "threashold": 7,
+        "threshold": 7,
         "resizeWidth": 700,
         "inputPath": None,
         "outputPath": None,
@@ -16,8 +20,16 @@ class Config:
         "avgNum": 10,
     }
 
-    def __init__(self):
+    def __init__(self, config_path):
         """This is basically just a wrapper for a json / python dict"""
+        if os.path.isfile(config_path):
+            print("using supplied configuration at", config_path)
+            # fail if config can not be parsed
+            with open(config_path) as file:
+                self.c = json.load(file)
+        else:
+            print("using default configuration")
+
         print("Current Config:")
         for key, value in self.c.items():
             print(f"{key}:\t\t{value}")

Application/ContourExctractor.py

@@ -29,7 +29,7 @@ class ContourExtractor:
         self.extracted_masks = dict()
         self.min_area = config["min_area"]
         self.max_area = config["max_area"]
-        self.threashold = config["threashold"]
+        self.threshold = config["threshold"]
         self.resize_width = config["resizeWidth"]
         self.video_path = config["inputPath"]
         self.x_dim = 0
@@ -74,7 +74,7 @@ class ContourExtractor:
 
         gray = self.prepare_frame(frame)
         frame_delta = cv2.absdiff(gray, first_frame)
-        thresh = cv2.threshold(frame_delta, self.threashold, 255, cv2.THRESH_BINARY)[1]
+        thresh = cv2.threshold(frame_delta, self.threshold, 255, cv2.THRESH_BINARY)[1]
         # dilate the thresholded image to fill in holes, then find contours
         thresh = cv2.dilate(thresh, None, iterations=10)
         # cv2.imshow("changes x", thresh)

README.md

@@ -34,7 +34,7 @@ On my configuration 1 minutes of of the original Video can be processed in about
 
         "min_area": 100,            min area in pixels, of a single contour, smaller is ignored
         "max_area": 9000000,        max area in pixels, of a single contour, larger is ignored
-        "threashold": 6,            luminance difference threashold, sensitivity of movement detection
+        "threshold": 6,            luminance difference threshold, sensitivity of movement detection
         "resizeWidth": 600,         video is scaled down internally
         "inputPath": None,          overwritten in main.py
         "outputPath": None,         overwritten in main.py

demo_config.json

@@ -0,0 +1,16 @@
+{
+  "min_area": 300,
+  "max_area": 900000,
+  "threshold": 7,
+  "resizeWidth": 700,
+  "inputPath": null,
+  "outputPath": null,
+  "maxLayerLength": 5000,
+  "minLayerLength": 40,
+  "tolerance": 20,
+  "maxLength": null,
+  "ttolerance": 50,
+  "videoBufferLength": 250,
+  "LayersPerContour": 220,
+  "avgNum": 10
+}

main.py

@@ -47,9 +47,11 @@ if __name__ == "__main__":
                         help='input video to extract movement from')
     parser.add_argument('output', metavar='output_dir', type=str, nargs="?", default="output",
                         help='output directory to save results and cached files into')
+    parser.add_argument('config', metavar='config', type=str, nargs="?", default=None,
+                        help='relative path to config.json')
     args = parser.parse_args()
 
-    config = Config()
+    config = Config(args.config)
 
     input_path = os.path.join(os.path.dirname(__file__), args.input)
     output_path = os.path.join(os.path.dirname(__file__), args.output)