From dfa904ed30921876df83d10085292a00c18b68fb Mon Sep 17 00:00:00 2001 From: Jani Jansson Date: Thu, 3 Aug 2023 12:01:17 +0300 Subject: [PATCH] Fixed the two Numpy alias deprecation errors in deep_sort.py and detection.py, updated README.md. --- README.md | 3 ++- deep_sort_pytorch/deep_sort/deep_sort.py | 2 +- deep_sort_pytorch/deep_sort/sort/detection.py | 2 +- 3 files changed, 4 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index dd1fa22..b32db3e 100644 --- a/README.md +++ b/README.md @@ -30,11 +30,12 @@ https://user-images.githubusercontent.com/37156032/160282244-42f6bd8c-bfc8-47af-
  • Clone this repo
  • Install all the dependencies
  • Download deepsort checkpoint file and paste it in deep_sort_pytorch/deep_sort/deep/checkpoint
  • -
  • Run -> streamlit run app.py
  • +
  • Run -> 'streamlit run app.py' or 'python -m streamlit run app.py' in Windows.
  • ## :star: Recent changelog
      +
    1. Fixed the errors related to Numpy 1.20.0 alias deprecations.
    2. Updated yolov5s weight file name in detect() in app.py
    3. Added drive link to download DeepSort checkpoint file (45Mb).
    diff --git a/deep_sort_pytorch/deep_sort/deep_sort.py b/deep_sort_pytorch/deep_sort/deep_sort.py index adb7d93..a856f5f 100644 --- a/deep_sort_pytorch/deep_sort/deep_sort.py +++ b/deep_sort_pytorch/deep_sort/deep_sort.py @@ -47,7 +47,7 @@ def update(self, bbox_xywh, confidences, ori_img): box = track.to_tlwh() x1, y1, x2, y2 = self._tlwh_to_xyxy(box) track_id = track.track_id - outputs.append(np.array([x1, y1, x2, y2, track_id], dtype=np.int)) + outputs.append(np.array([x1, y1, x2, y2, track_id], dtype=np.int32)) if len(outputs) > 0: outputs = np.stack(outputs, axis=0) return outputs diff --git a/deep_sort_pytorch/deep_sort/sort/detection.py b/deep_sort_pytorch/deep_sort/sort/detection.py index 5c884bb..e598da8 100644 --- a/deep_sort_pytorch/deep_sort/sort/detection.py +++ b/deep_sort_pytorch/deep_sort/sort/detection.py @@ -27,7 +27,7 @@ class Detection(object): """ def __init__(self, tlwh, confidence, feature): - self.tlwh = np.asarray(tlwh, dtype=np.float) + self.tlwh = np.asarray(tlwh, dtype=np.float32) self.confidence = float(confidence) self.feature = np.asarray(feature, dtype=np.float32)