working on bdcn postprocessing

playground/bdcn_postprocessing.py

@@ -7,6 +7,10 @@ from sys import platform
 from dotmap import DotMap
 from shapely.geometry import Polygon
 from shapely import affinity
+from openpose import pyopenpose as op
+params = dict()
+#params["model_folder"] = "/Users/Tilman/Documents/Programme/Python/forschungspraktikum/openpose/models/"
+params["model_folder"] = os.environ['OPENPOSE_MODELS']
 
 # from openpose import pyopenpose as op
 
@@ -35,32 +39,65 @@ images.sort()
 images_bdcn.sort()
 # os.chdir('../images/out/images_imdahl/filtered_median/') #save images in this dir
 
-datum = DotMap()
-datum.poseKeypoints = OPENPOSE_DEMO_KEYPOINTS
+#datum = DotMap()
+#datum.poseKeypoints = OPENPOSE_DEMO_KEYPOINTS
 
-for img_name, img_bdcn in list(zip(images, images_bdcn))[15:16]: #christus only
+opWrapper = op.WrapperPython()
+opWrapper.configure(params)
+opWrapper.start()
+
+for img_name, img_bdcn in list(zip(images, images_bdcn)): #christus only
     img = cv2.imread(img_name)
     bdcn = cv2.imread(img_bdcn)
     max_lw = max(len(img),len(img[0]))
     esz = max_lw / DISPLAY_RASTER_ELEMENTS
 
+    datum = op.Datum()
+    datum.cvInputData = img
+    opWrapper.emplaceAndPop([datum])
+
     fposes = np.array([np.array([line[:2] for line in pose if line[2] > 0]) for pose in datum.poseKeypoints]) #filtered poses without zero lines
     
     print("fposes",fposes)
+    #draw out poses
     for pose in fposes:
         convexhull = Polygon(pose).convex_hull
-        sconvexhull = affinity.scale(convexhull, xfact=1.7, yfact=2, origin=convexhull.centroid)
+        sconvexhull = affinity.scale(convexhull, xfact=1.4, yfact=2, origin=convexhull.centroid)
         print(convexhull)
         #cv2.line(img, (int(pose[0][0]),int(pose[0][1])), (int(pose[1][0]),int(pose[1][1])), (0,255,0), int(6*esz))
-        cv2.drawContours(img, [polyToArr(sconvexhull)], 0, 255, int(20*esz))
+        cv2.drawContours(img, [polyToArr(sconvexhull)], 0, 255, int(10*esz))
         cv2.drawContours(img, [polyToArr(sconvexhull)], 0, 255, -1)
-        cv2.drawContours(bdcn, [polyToArr(sconvexhull)], 0, (255,255,255), int(20*esz))
+        cv2.drawContours(bdcn, [polyToArr(sconvexhull)], 0, (255,255,255), int(10*esz))
         cv2.drawContours(bdcn, [polyToArr(sconvexhull)], 0, (255,255,255), -1)
-    
+    #draw rectangle
+    cv2.rectangle(img, (0,0), (len(img[0]),len(img)), (255,0,0), int(40*esz))
+    cv2.rectangle(bdcn, (0,0), (len(img[0]),len(img)), (255,255,255), int(40*esz))
 
     cv2.namedWindow(img_name, cv2.WINDOW_NORMAL)
     cv2.namedWindow(img_name+'bdcn', cv2.WINDOW_NORMAL)
+    cv2.namedWindow(img_name+'blurred', cv2.WINDOW_NORMAL)
+
+    rho=10
+    theta=180
+    threshold=2950
+    minline=int(max_lw/4) #minline 1/6 of image width/heigth
+    maxgap=int(max_lw/50) #minline 1/12 of image width/heigth
+    print("params",rho,theta,threshold,minline,maxgap)
+    #blurred = bdcn.copy()
+    #cv2.imshow(img_name+'blurred', blurred)
+    gray = cv2.cvtColor(bdcn, cv2.COLOR_BGR2GRAY)
+    blurred = cv2.GaussianBlur(gray,(5,5),0)
+    # cv2.imshow(img_name+'blurred', blurred)
+    # cv2.waitKey(0)
+    lines = cv2.HoughLinesP(image=blurred, rho=rho, theta=np.pi/theta, threshold=threshold, minLineLength=minline, maxLineGap=maxgap)
+    # if(lines):
+    if lines is not None:
+        for line in lines:
+            x1, y1, x2, y2 = line[0]
+            cv2.line(bdcn, (x1, y1), (x2, y2), (255, 0, 0), 3)
+    
     cv2.imshow(img_name, img)
+    cv2.imshow(img_name+'blurred', blurred)
     cv2.imshow(img_name+'bdcn', bdcn)
     cv2.waitKey(0)
 

playground/threshold_slider.py

@@ -54,7 +54,7 @@ def on_maxgap(val):
     update()
 def update():
     image = cv.imread('../images/out/fuse_1_bsds500/1.png')
-    lines = cv.HoughLinesP(image=auto, rho=rho, theta=np.pi/theta, threshold=threshold, minLineLength=minline, maxLineGap=maxgap)
+    lines = cv.HoughLinesP(image=image, rho=rho, theta=np.pi/theta, threshold=threshold, minLineLength=minline, maxLineGap=maxgap)
     # if(lines):
     if lines is not None:
         for line in lines: