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All Necessary Changes to run on latest versions #308

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All Necessary Changes to run on latest versions #308

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d017ecd
Commit tf2 compat
Dipankar1997161 Mar 13, 2023
7b6b853
2 Modifications commit
Dipankar1997161 Mar 13, 2023
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3 changes: 2 additions & 1 deletion deep_sort/linear_assignment.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
# vim: expandtab:ts=4:sw=4
from __future__ import absolute_import
import numpy as np
from sklearn.utils.linear_assignment_ import linear_assignment
from scipy.optimize import linear_sum_assignment as linear_assignment
from . import kalman_filter


Expand Down Expand Up @@ -56,6 +56,7 @@ def min_cost_matching(
tracks, detections, track_indices, detection_indices)
cost_matrix[cost_matrix > max_distance] = max_distance + 1e-5
indices = linear_assignment(cost_matrix)
indices = np.hstack([indices[0].reshape(((indices[0].shape[0]), 1)),indices[1].reshape(((indices[0].shape[0]), 1))])

matches, unmatched_tracks, unmatched_detections = [], [], []
for col, detection_idx in enumerate(detection_indices):
Expand Down
16 changes: 8 additions & 8 deletions tools/generate_detections.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,15 +72,15 @@ class ImageEncoder(object):

def __init__(self, checkpoint_filename, input_name="images",
output_name="features"):
self.session = tf.Session()
with tf.gfile.GFile(checkpoint_filename, "rb") as file_handle:
graph_def = tf.GraphDef()
self.session = tf.compat.v1.Session()
with tf.compat.v1.gfile.GFile(checkpoint_filename, "rb") as file_handle:
graph_def = tf.compat.v1.GraphDef()
graph_def.ParseFromString(file_handle.read())
tf.import_graph_def(graph_def, name="net")
self.input_var = tf.get_default_graph().get_tensor_by_name(
"net/%s:0" % input_name)
self.output_var = tf.get_default_graph().get_tensor_by_name(
"net/%s:0" % output_name)
tf.compat.v1.import_graph_def(graph_def, name="net")
self.input_var = tf.compat.v1.get_default_graph().get_tensor_by_name(
"%s:0" % input_name) #"net/%s:0" % input_name
self.output_var = tf.compat.v1.get_default_graph().get_tensor_by_name(
"%s:0" % output_name) #"net/%s:0" % output_name

assert len(self.output_var.get_shape()) == 2
assert len(self.input_var.get_shape()) == 4
Expand Down