Col classify 0

.gitignore

@@ -0,0 +1,139 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+.vscode
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/

README.md

@@ -55,6 +55,9 @@ python save_model.py --model yolov4
 # Run yolov4 deep sort object tracker on video
 python object_tracker.py --video ./data/video/test.mp4 --output ./outputs/demo.avi --model yolov4
 
+# footbal
+python object_tracker.py --video data/video/football1.mp4 --output outputs/football1.mp4
+
 # Run yolov4 deep sort object tracker on webcam (set video flag to 0)
 python object_tracker.py --video 0 --output ./outputs/webcam.avi --model yolov4
 ```

extract_pixel_pos.py

@@ -0,0 +1,52 @@
+import cv2 as cv
+import sys
+
+ref_points=[]
+
+def get_point(event,x,y,flags,param):
+    if event == cv.EVENT_LBUTTONDOWN:
+        print("x={},y={}".format(x,y))
+        xy="%d,%d"%(x,y)
+        ref_points.append((x,y))
+        cv.circle(frame, (x, y), 1, (255, 0, 0), thickness = 1)
+        cv.putText(frame,xy,(x,y),cv.FONT_HERSHEY_PLAIN,2.0,(0,0,0),thickness=2)
+        cv.imshow('Soccer',frame)
+
+
+file_name=sys.argv[1].split('.')
+if file_name[1]=='mp4':
+    video_capture=cv.VideoCapture(sys.argv[1])
+    fps = int(video_capture.get(cv.CAP_PROP_FPS))
+    width = int(video_capture.get(cv.CAP_PROP_FRAME_WIDTH))
+    height = int(video_capture.get(cv.CAP_PROP_FRAME_HEIGHT))
+    print("fps:", fps)
+    print("width:", width)
+    print("height:", height)
+    ret_val,frame=video_capture.read()
+    if ret_val:
+        cv.namedWindow('Soccer',cv.WINDOW_NORMAL)
+        cv.setMouseCallback('Soccer',get_point)
+    else:
+        print("error get frame")
+elif file_name[1]=='png' or file_name[1]=='jpg':
+    frame=cv.imread(sys.argv[1])
+    cv.namedWindow('Soccer',cv.WINDOW_NORMAL)
+    cv.setMouseCallback('Soccer',get_point)
+
+def extract_points():
+    while 1:
+        cv.imshow('Soccer',frame)
+        k=cv.waitKey(1)&0xFF #the wait key must put here
+        if not cv.getWindowProperty('Soccer',cv.WND_PROP_VISIBLE):
+            break
+        if k==27:
+            break
+    cv.destroyAllWindows()
+    return ref_points
+
+#cmd example
+#python extract_pixel_pos.py data/video/id3_500f.mp4
+#
+if __name__=="__main__":
+    extract_points()
+    print(ref_points)

object_tracker.py

@@ -23,6 +23,7 @@
 from deep_sort.detection import Detection
 from deep_sort.tracker import Tracker
 from tools import generate_detections as gdet
+import collections
 flags.DEFINE_string('framework', 'tf', '(tf, tflite, trt')
 flags.DEFINE_string('weights', './checkpoints/yolov4-416',
                     'path to weights file')
@@ -38,6 +39,54 @@
 flags.DEFINE_boolean('info', False, 'show detailed info of tracked objects')
 flags.DEFINE_boolean('count', False, 'count objects being tracked on screen')
 
+
+def getColorList():
+    dict = collections.defaultdict(list)
+
+    # 白色
+    lower_white = np.array([0, 0, 221])
+    upper_white = np.array([180, 30, 255])
+    color_list = []
+    color_list.append(lower_white)
+    color_list.append(upper_white)
+    color_list.append([248, 248, 255])
+    dict['white'] = color_list
+
+
+    #蓝色
+    lower_blue = np.array([100, 43, 46])
+    upper_blue = np.array([124, 255, 255])
+    color_list = []
+    color_list.append(lower_blue)
+    color_list.append(upper_blue)
+    color_list.append([0, 0, 221])
+    dict['blue'] = color_list
+
+    return dict
+
+def get_color(frame):
+    hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
+    maxsum = -100
+    color = None
+    color_dict = getColorList()
+    for d in color_dict:
+        mask = cv2.inRange(hsv,color_dict[d][0],color_dict[d][1])
+        #binary = cv2.threshold(mask, 127, 255, cv2.THRESH_BINARY)[1]
+        #binary = cv2.dilate(binary,None,iterations=2)
+        #cnts, hiera = cv2.findContours(binary.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
+        s = sum(mask.flatten())
+        #for c in cnts:
+        #    sum+=cv2.contourArea(c)
+        if s > maxsum :
+            maxsum = s
+            color = d
+    if(color=='blue'):
+        for d in color_dict:
+            mask = cv2.inRange(hsv,color_dict[d][0],color_dict[d][1])
+            print(sum(mask.flatten()))
+
+    return color
+
 def main(_argv):
     # Definition of the parameters
     max_cosine_distance = 0.4
@@ -90,10 +139,14 @@ def main(_argv):
         codec = cv2.VideoWriter_fourcc(*FLAGS.output_format)
         out = cv2.VideoWriter(FLAGS.output, codec, fps, (width, height))
 
+    color_dict = getColorList()
     frame_num = 0
+
     # while video is running
     while True:
         return_value, frame = vid.read()
+        pic = frame.copy()
+        cv2.imwrite("pic.png", pic)
         if return_value:
             frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
             image = Image.fromarray(frame)
@@ -157,8 +210,9 @@ def main(_argv):
         class_names = utils.read_class_names(cfg.YOLO.CLASSES)
 
         # by default allow all classes in .names file
-        allowed_classes = list(class_names.values())
-
+        #allowed_classes = list(class_names.values())
+        allowed_classes = ['person', 'sports ball']
+        # allowed_classes = ['sports ball']
         # custom allowed classes (uncomment line below to customize tracker for only people)
         #allowed_classes = ['person']
 
@@ -205,14 +259,25 @@ def main(_argv):
             if not track.is_confirmed() or track.time_since_update > 1:
                 continue 
             bbox = track.to_tlbr()
-            class_name = track.get_class()
-
+            #class_name = track.get_class()
+            class_name = str(track.track_id)
+
         # draw bbox on screen
-            color = colors[int(track.track_id) % len(colors)]
-            color = [i * 255 for i in color]
-            cv2.rectangle(frame, (int(bbox[0]), int(bbox[1])), (int(bbox[2]), int(bbox[3])), color, 2)
-            cv2.rectangle(frame, (int(bbox[0]), int(bbox[1]-30)), (int(bbox[0])+(len(class_name)+len(str(track.track_id)))*17, int(bbox[1])), color, -1)
-            cv2.putText(frame, class_name + "-" + str(track.track_id),(int(bbox[0]), int(bbox[1]-10)),0, 0.75, (255,255,255),2)
+            #color = colors[int(track.track_id) % len(colors)]
+            #color = [i * 255 for i in color]
+            cv2.imwrite("p"+str(track.track_id)+".png", pic[int(max(0,min(bbox[1],bbox[3]))):int(max(bbox[1],bbox[3])), int(max(min(bbox[0],bbox[2]),0)):int(max(bbox[2],bbox[0]))])
+            color = get_color(pic[int(max(0,min(bbox[1],bbox[3]))):int(max(bbox[1],bbox[3])), int(max(min(bbox[0],bbox[2]),0)):int(max(bbox[2],bbox[0]))])
+            temp = []
+            for i in color_dict[color][2]:
+                temp.append(int(i))
+            if color=='blue':
+                print(track.track_id)
+            if(len(frame)*0.5<= abs(int(bbox[1]-bbox[3]))):
+                continue
+            cv2.rectangle(frame, (int(bbox[0]), int(bbox[1])), (int(bbox[2]), int(bbox[3])), temp, 2)
+            cv2.rectangle(frame, (int(bbox[0]), int(bbox[1]-5)), (int(bbox[0])+(len(class_name)+len(str(track.track_id)))*7, int(bbox[1])), temp, -1)
+            #cv2.putText(frame, class_name + "-" + str(track.track_id),(int(bbox[0]), int(bbox[1]-10)),0, 0.3, (255,255,255),2)
+            cv2.putText(frame, class_name,(int(bbox[0]), int(bbox[1]-10)),0, 0.3, (255,255,255),2)
 
         # if enable info flag then print details about each track
             if FLAGS.info:

perspective_transfrom.py

@@ -0,0 +1,52 @@
+import cv2
+import sys
+import numpy as np
+
+video_center_point=np.array([940,397],dtype='float32')
+video_points=np.array([[1431, 397], [450, 397], [940, 97], [940, 1022]],dtype='float32')
+row,col=video_points.shape
+for i in range(row):
+    video_points[i]-=video_center_point
+
+soccer_field_center=np.array([512,327],dtype='float32')
+soccer_field_points=np.array([[594,327],[429,327],[512,26],[512,626]],dtype='float32')
+row,col=soccer_field_points.shape
+for i in range(row):
+    soccer_field_points[i]-=soccer_field_center
+
+soccer_filed_img=cv2.imread('data/video/Soccer_field.png')
+M=cv2.getPerspectiveTransform(video_points,soccer_field_points)
+#print(M)
+
+#input a tuple return a tuple
+def perspective_transform(people_point):
+    (x,y)=people_point
+    people_point=np.array([x,y],dtype='float32')
+    people_point-=video_center_point
+    people_point=np.r_[people_point,1] #insert in row
+    #print(people_point.shape)
+
+    dst_people_point=np.dot(M,people_point)
+    dst_people_point=dst_people_point[0:2]
+    dst_people_point+=soccer_field_center
+    (x,y)=(int(dst_people_point[0]),int(dst_people_point[1]))
+    return (x,y)
+    #print((x,y))
+
+if __name__=="__main__":
+    #dst_people_point=cv2.perspectiveTransform(people_point.T,M)
+    cv2.namedWindow('Perspective',cv2.WINDOW_NORMAL)
+    soccer_filed_img=cv2.imread('data/video/Soccer_field.png')
+    print(soccer_filed_img.shape)
+    (x,y)=perspective_transform((1276,284)) #a simpl people example, remember to input the foot point
+    cv2.circle(soccer_filed_img,(x,y),5,(255,0,0),thickness=3)
+    while 1:
+        cv2.imshow('Perspective',soccer_filed_img)
+        # k=cv2.waitKey(1)&0xFF #the wait key must put here
+        # if not cv2.getWindowProperty('Perspective',cv2.WND_PROP_VISIBLE):
+        #     break
+        if cv2.waitKey(0)&0xFF==27:
+            break
+        cv2.destroyAllWindows()
+
+