From 530022ec1daf17c641ef0a41c106655b5c63a568 Mon Sep 17 00:00:00 2001 From: kXborg Date: Sun, 8 Dec 2024 23:01:31 +0530 Subject: [PATCH 1/2] removed deprecated np.float --- yolox/tracker/byte_tracker.py | 2 +- yolox/tracker/matching.py | 12 ++++++------ 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/yolox/tracker/byte_tracker.py b/yolox/tracker/byte_tracker.py index 2d004599..626c3a90 100644 --- a/yolox/tracker/byte_tracker.py +++ b/yolox/tracker/byte_tracker.py @@ -15,7 +15,7 @@ class STrack(BaseTrack): def __init__(self, tlwh, score): # wait activate - self._tlwh = np.asarray(tlwh, dtype=np.float) + self._tlwh = np.asarray(tlwh, dtype=np.float64) self.kalman_filter = None self.mean, self.covariance = None, None self.is_activated = False diff --git a/yolox/tracker/matching.py b/yolox/tracker/matching.py index d36a6cf5..2572c4d1 100644 --- a/yolox/tracker/matching.py +++ b/yolox/tracker/matching.py @@ -58,13 +58,13 @@ def ious(atlbrs, btlbrs): :rtype ious np.ndarray """ - ious = np.zeros((len(atlbrs), len(btlbrs)), dtype=np.float) + ious = np.zeros((len(atlbrs), len(btlbrs)), dtype=np.float64) if ious.size == 0: return ious ious = bbox_ious( - np.ascontiguousarray(atlbrs, dtype=np.float), - np.ascontiguousarray(btlbrs, dtype=np.float) + np.ascontiguousarray(atlbrs, dtype=np.float64), + np.ascontiguousarray(btlbrs, dtype=np.float64) ) return ious @@ -118,13 +118,13 @@ def embedding_distance(tracks, detections, metric='cosine'): :return: cost_matrix np.ndarray """ - cost_matrix = np.zeros((len(tracks), len(detections)), dtype=np.float) + cost_matrix = np.zeros((len(tracks), len(detections)), dtype=np.float64) if cost_matrix.size == 0: return cost_matrix - det_features = np.asarray([track.curr_feat for track in detections], dtype=np.float) + det_features = np.asarray([track.curr_feat for track in detections], dtype=np.float64) #for i, track in enumerate(tracks): #cost_matrix[i, :] = np.maximum(0.0, cdist(track.smooth_feat.reshape(1,-1), det_features, metric)) - track_features = np.asarray([track.smooth_feat for track in tracks], dtype=np.float) + track_features = np.asarray([track.smooth_feat for track in tracks], dtype=np.float64) cost_matrix = np.maximum(0.0, cdist(track_features, det_features, metric)) # Nomalized features return cost_matrix From 2ee2e79b0baf14c70ba0e54ae78c74443a1bfa95 Mon Sep 17 00:00:00 2001 From: kXborg Date: Mon, 9 Dec 2024 00:07:06 +0530 Subject: [PATCH 2/2] version update --- requirements.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/requirements.txt b/requirements.txt index aae46682..869dbf26 100644 --- a/requirements.txt +++ b/requirements.txt @@ -17,6 +17,6 @@ filterpy h5py # verified versions -onnx==1.8.1 -onnxruntime==1.8.0 +onnx==1.17.0 +onnxruntime==1.20.1 onnx-simplifier==0.3.5