Add video support

CSRT/CSRT.py

@@ -143,6 +143,10 @@ def calculate_g_cap_and_channel_weights(self):
             G = np.fft.ifft2(res)
             G = (G - G.min()) / (G.max() - G.min())
             self.G_cap[channel_index] = G
+            print("In calc", self.G_cap)
+            print("res", res)
+            print("f_hat", f_hat)
+            print("self.h_cap", self.h_cap)
 
             max_value = np.max(G)
             G_nms = []
@@ -169,29 +173,38 @@ def calculate_g_cap_and_channel_weights(self):
             print("roi", self.roi)
             print('G shape', self.features[0].shape)
 
-    def calculate_final_g_cap(self):
-        for channel_index in range(len(self.features)):
-            self.G_res += self.G_cap[channel_index] * self.channel_weights[channel_index]
-        return self.G_res
+    # def calculate_final_g_cap(self):
+    #     for channel_index in range(len(self.features)):
+    #         self.G_res += self.G_cap[channel_index] * self.channel_weights[channel_index]
+    #     return self.G_res
 
     def draw_bbox(self):
         self.G_res = self.G_cap[0] * self.channel_weights[0]
+        print("self.G_res before", self.G_res)
+        print("self.G_cap", self.G_cap)
+        print("channel w", self.channel_weights)
         for channel_index in range(1, len(self.features)):
             self.G_res += self.G_cap[channel_index] * self.channel_weights[channel_index]
-        self.G_res = (self.G_res - self.G_res.min()) / (self.G_res.max() - self.G_res.min())
+        if (self.G_res.max() - self.G_res.min() != 0):
+            self.G_res = (self.G_res - self.G_res.min()) / (self.G_res.max() - self.G_res.min())
         max_value = np.max(self.G_res)
         max_pos = np.where(self.G_res == max_value)
+        print("max_pos", max_pos)
+        print("self.G_res", self.G_res)
+        print("max_value", max_value)
         dy = int(np.mean(max_pos[0]) - self.G_res.shape[0] / 2)
         dx = int(np.mean(max_pos[1]) - self.G_res.shape[1] / 2)
         self.p = [self.x + dx, self.y + dy, self.x + dx + self.width, self.y + dy + self.height]
-        print(self.p[0])
-        print(self.p[1])
-        print(self.p[2])
-        print(self.p[3])
+        self.p = [int(k) for k in self.p]
+        # print(self.p[0])
+        # print(self.p[1])
+        # print(self.p[2])
+        # print(self.p[3])
         cv2.rectangle(self.frame, (self.p[0], self.p[1]), (self.p[2], self.p[3]), (0, 255, 0), 2)
         cv2.imshow("frame", self.frame)
-        cv2.waitKey(0)
-        cv2.destroyAllWindows()
+        cv2.waitKey(100)
+        # cv2.destroyAllWindows()
+        return self.p
 
     def apply_csrt(self):
         pass

CSRT/HOG_features.py

@@ -3,13 +3,14 @@
 import numpy as np
 
 def get_hog_features(image, des_orientations, des_pixels_per_cell):
-    fd, hog_image = hog(image, orientations = des_orientations,
-        pixels_per_cell = (des_pixels_per_cell, des_pixels_per_cell), cells_per_block=(2, 2),
-        visualize=True,multichannel=True)
+    fd, hog_image = hog(image, orientations = des_orientations, pixels_per_cell = (image.shape[0] / 100, image.shape[1] / 100), cells_per_block=(2, 2), visualize=True,multichannel=True)
     # np.resize(fd, hog_image.shape)
     # print("fd shape", fd.shape)
     # print("hog shape", hog_image.shape)
     # cv2.imshow("Hog image", hog_image)
     # cv2.waitKey(0)
     # cv2.destroyAllWindows()
     return hog_image
+
+
+

CSRT/test.py

@@ -2,35 +2,47 @@
 from CSRT import *
 
 
-img = cv2.imread('/home/prathamesh/OpenCV-Trackers/assets/dog_test.png')
-roi = cv2.selectROI('select roi',img)
+# img = cv2.imread('/home/prathamesh/OpenCV-Trackers/assets/dog_test.png')
+# roi = cv2.selectROI('select roi',img)
+# # print(roi)
+# # print(type(roi))
+# # print(type(img))
+# # print(img.shape)
 # print(roi)
-# print(type(roi))
-# print(type(img))
-# print(img.shape)
 
-tracker = CSRT(img, roi, 20)
-tracker.set_roiImage()
-tracker.get_spatial_reliability_map()
-tracker.generate_features(8, 2)
-tracker.update_H()
-tracker.calculate_g_cap_and_channel_weights()
-tracker.draw_bbox()
+# tracker = CSRT(img, roi, 40)
+# tracker.set_roiImage()
+# tracker.get_spatial_reliability_map()
+# tracker.generate_features(8, 2)
+# tracker.update_H()
+# tracker.calculate_g_cap_and_channel_weights()
+# next_roi = tuple(tracker.draw_bbox())
+# print(next_roi)
+
+video = cv2.VideoCapture("/home/prathamesh/OpenCV-Trackers/assets/chaplin.mp4")
+
+_, frame1 = video.read()
+roi = cv2.selectROI('Select Roi', frame1)
+# tracker = CSRT(frame1, roi, 10)
+while(video.isOpened()):
+    _, frame = video.read()
+    print("roi ", roi)
+    tracker = CSRT(frame, roi, 1)
+    tracker.set_roiImage()
+    tracker.get_spatial_reliability_map()
+    tracker.generate_features(8, 2)
+    tracker.update_H()
+    tracker.calculate_g_cap_and_channel_weights()
+    print("Here")
+    roi = tuple(tracker.draw_bbox())
+    print("Here too")
+    print("roi", roi)
+
+
+# tracker.set_roiImage()
+# tracker.get_spatial_reliability_map()
+# tracker.generate_features(8, 2)
+# tracker.update_H()
+# tracker.calculate_g_cap_and_channel_weights()
+# roi = tuple(tracker.draw_bbox())
 
-# video = cv2.VideoCapture("/home/prathamesh/OpenCV-Trackers/assets/chaplin.mp4")
-
-# tracker = CSRT(5)
-# _, frame1 = video.read()
-# roi = cv2.selectROI('Select Roi', frame1)
-# tracker.next_frame(frame1, roi)
-
-# while(video.isOpened()):
-#     pass
-
-
-# tracker.apply_csrt()
-
-# x, y, w, h = tracker.get_new_roi()
-# cv2.rectangle(img, (x, y),(x + w, y + h), (0,255,0), 2)
-# cv2.imshow('csrt',img)
-# cv2.waitKey(0)