Merge pull request #2 from yanndebray/main

Improvements coming with Python Importer for Simulink

Author: yanndebray

.gitattributes

@@ -0,0 +1,28 @@
+* text=auto
+
+*.fig binary
+*.mat binary
+*.mdl binary diff merge=mlAutoMerge
+*.mdlp binary
+*.mex* binary
+*.mlapp binary
+*.mldatx binary
+*.mlproj binary
+*.mlx binary
+*.p binary
+*.sfx binary
+*.sldd binary
+*.slreqx binary merge=mlAutoMerge
+*.slmx binary merge=mlAutoMerge
+*.sltx binary
+*.slxc binary
+*.slx binary merge=mlAutoMerge
+*.slxp binary
+
+## Other common binary file types
+*.docx binary
+*.exe binary
+*.jpg binary
+*.pdf binary
+*.png binary
+*.xlsx binary

.gitignore

@@ -0,0 +1,2 @@
+__pycache__/
+slprj/

HumanDetection.slx

@@ -0,0 +1,33 @@
+{
+ "SimulinkCodeImporterVersion": 1,
+ "LibraryFileName": "HumanDetection",
+ "CustomCode": {
+ "SourceFiles": ".\\detectHuman.py",
+ "GlobalVariableInterface": false
+ },
+ "FunctionsToImport": "detectHuman.detectHumanFromFrame",
+ "FunctionSettings": {
+ "Name": "detectHuman.detectHumanFromFrame",
+ "PortSpecArray": [
+ {
+ "ArgName": "image",
+ "PortName": "image",
+ "Scope": "Output",
+ "Index": "1",
+ "Type": "uint8",
+ "Size": "[300 400 3]",
+ "IsGlobal": false
+ },
+ {
+ "ArgName": "image",
+ "PortName": "image",
+ "Scope": "Input",
+ "Index": "1",
+ "Type": "uint8",
+ "Size": "[480 640 3]",
+ "IsGlobal": false
+ }
+ ],
+ "IsDeterministic": false
+ }
+}

HumanDetection_import.json

@@ -1,22 +1,18 @@
 import time
-import imutils
+# import imutils
 import numpy as np
-from cv2 import cv2
+import cv2
+import hogClass
 
+def detectHumanFromFrame(image):
 
-class hogObject:
- detector = cv2.HOGDescriptor()
- def __init__(self):
- self.detector.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
-
-
-def getHogObject():
- return hogObject()
-
-
-def detectHumanFromFrame(image, hog):
+ hog = hogClass.hogObject()
+ 
  image = np.asarray(image)
- image = imutils.resize(image, width=min(400, image.shape[1]))
+ # image = imutils.resize(image, width=min(400, image.shape[1]))
+ ratio = image.shape[0] / image.shape[1]
+ new_height = int(400 * ratio)
+ image = cv2.resize(image, (400,new_height))
 
  # Detecting all the regions in the Image that has a pedestrians inside it
  (regions, _) = hog.detector.detectMultiScale(
@@ -30,8 +26,6 @@ def detectHumanFromFrame(image, hog):
 
 
 if __name__ == "__main__":
-
- hog = hogObject()
 
  cap = cv2.VideoCapture('livedata.mp4')
  ret, image = cap.read()
@@ -41,7 +35,7 @@ def detectHumanFromFrame(image, hog):
  # Reading the video stream
  ret, image = cap.read()
  if ret:
- image = detectHumanFromFrame(image, hog)
+ image = detectHumanFromFrame(image)
  cv2.imshow("Image", image)
  cv2.waitKey(5)
  if cv2.waitKey(5) & 0xFF == ord('q'):