Issue with siamese_track( )

whenever I clone and use this repo in my notebook. It generates error with this line

**state = siamese_track(state, frame, mask_enable=True, refine_enable=True, device=device)**

**error message is:**
AttributeError: module 'numpy' has no attribute 'float'.
`np.float` was a deprecated alias for the builtin `float`. To avoid this error in existing code, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

**Apparently** it seems, I am using newer version of numpy and use of np.float has been deprecated. I have tried out these.

1. I have tried to rerun (on my local machine) with older version of numpy from my activated virtual env, but no use.
2. In Google colab, i have tried to forcefully pip install older version of numpy, it didn't work too.
3. I tried to replace all occurrences of np.float with float, but didn't work.
4. i tried to replace all occurrences of np.float64, but it didn't work too.
Now what to do?

**Secondly,** in some codes( as in this code), apparently there is no np.float present in our code. It might be possible that definition of siamese_track is using it, but how to locate that definition in entire repo? or should I search for it in all possible .py and .ipnb files that are present in this repo, but how is that possible

**My code cell is given below.**
**steps:**
**1: Mount drive** - running
**2: Setting up imports, Clone and Install Darknet (Yolov4) and SiamMask, copying weights** - running

**3: Detect the object using Yolov4 and track it using SiamMask;** -- generating error

def YoloSiam():
f = 0
video_capture = cv2.VideoCapture()
if video_capture.open('target.mp4'):
width, height = int(video_capture.get(cv2.CAP_PROP_FRAME_WIDTH)), int(video_capture.get(cv2.CAP_PROP_FRAME_HEIGHT))
fps = video_capture.get(cv2.CAP_PROP_FPS)

!rm -f output.mp4 output.avi
# can't write out mp4, so try to write into an AVI file
video_writer = cv2.VideoWriter("output.avi", cv2.VideoWriter_fourcc(*'MJPG'), fps, (width, height))

while video_capture.isOpened():
ret, frame = video_capture.read()
if not ret:
break

if f == 0:

# detect the object using Yolov4

#moving into darknet directory
os.chdir('/content/darknet')

#saving file name to a txt file
im='first_frame.jpg'
with open('image.txt', 'w') as txt_file:
cv2.imwrite(im,frame)
txt_file.write(im)
im = cv2.imread(im)

#Running Yolov4 and creating json file
!./darknet detector test cfg/coco.data cfg/yolov4.cfg yolov4.weights -ext_output -dont_show -out result.json < image.txt

# Reading json file
json_file = open("result.json")
data = json.load(json_file)
json_file.close()

#Extracting relative coordinates from the json file
relative_coordinates=data[0]['objects'][0]['relative_coordinates']
rel_center_x=relative_coordinates['center_x']
rel_center_y=relative_coordinates['center_y']
rel_width=relative_coordinates['width']
rel_height=relative_coordinates['height']

#finding width and height of the image
img_height, img_width, c= im.shape

#Calculating absolute coordinates
w=math.ceil(rel_width*img_width)
h=math.ceil(rel_height*img_height)
x=math.ceil(rel_center_x*img_width-w/2) #top left
y=math.ceil(rel_center_y*img_height-h/2) #top left

#moving back to root directory
os.chdir('/content')

# init SiamMask tracker
target_pos, target_sz = None, None
target_pos = np.array([x + w / 2, y + h / 2])
target_sz = np.array([w, h])
state = siamese_init(frame, target_pos, target_sz, siammask, cfg['hp'], device=device)
else:
# track
state = siamese_track(state, frame, mask_enable=True, refine_enable=True, device=device)
location = state['ploygon'].flatten()
mask = state['mask'] > state['p'].seg_thr

frame[:, :, 2] = (mask > 0) * 255 + (mask == 0) * frame[:, :, 2]
cv2.polylines(frame, [np.int0(location).reshape((-1, 1, 2))], True, (0, 255, 0), 3)

video_writer.write(frame)

f += 1
# only on first 200 frames
if f > 200:
break

video_capture.release()
video_writer.release()

# convert AVI to MP4
!ffmpeg -y -loglevel info -i output.avi output.mp4
else:
print("can't open the given input video file!")

YoloSiamTime = %timeit -o -n 1 YoloSiam()

**Complete Error Message :**
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
[](https://localhost:8080/#) in ()
86 print("can't open the given input video file!")
87
---> 88 YoloSiamTime = get_ipython().run_line_magic('timeit', '-o -n 1 YoloSiam()')
89
90 #show video using the helping function defined in #2

8 frames
in timeit(self, line, cell, local_ns)

in inner(_it, _timer)

[/usr/local/lib/python3.10/dist-packages/numpy/__init__.py](https://localhost:8080/#) in __getattr__(attr)
317
318 if attr in __former_attrs__:
--> 319 raise AttributeError(__former_attrs__[attr])
320
321 if attr == 'testing':

AttributeError: module 'numpy' has no attribute 'float'.
`np.float` was a deprecated alias for the builtin `float`. To avoid this error in existing code, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

Start at the siamese_track call in the notebook and search the repository's Python and notebook files for np.float, including the tracker definition and its dependencies. Done means the reported tracking workflow runs without the NumPy AttributeError.

Written by the indexing model from the issue text.