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PyCharm Code and Docs Inspect fixes v1 (#18461)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Ultralytics Assistant <135830346+UltralyticsAssistant@users.noreply.github.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
This commit is contained in:
Muhammad Rizwan Munawar 2025-01-03 01:16:18 +05:00 • committed by GitHub
parent 126867e355
commit 7f1a50e893
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26 changed files with 90 additions and 91 deletions
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24
ultralytics/trackers/utils/gmc.py
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@ -26,9 +26,9 @@ class GMC:
Methods:
__init__: Initializes a GMC object with the specified method and downscale factor.
apply: Applies the chosen method to a raw frame and optionally uses provided detections.
applyEcc: Applies the ECC algorithm to a raw frame.
applyFeatures: Applies feature-based methods like ORB or SIFT to a raw frame.
applySparseOptFlow: Applies the Sparse Optical Flow method to a raw frame.
apply_ecc: Applies the ECC algorithm to a raw frame.
apply_features: Applies feature-based methods like ORB or SIFT to a raw frame.
apply_sparseoptflow: Applies the Sparse Optical Flow method to a raw frame.
reset_params: Resets the internal parameters of the GMC object.
Examples:
@ -108,15 +108,15 @@ class GMC:
(480, 640, 3)
"""
if self.method in {"orb", "sift"}:
return self.applyFeatures(raw_frame, detections)
return self.apply_features(raw_frame, detections)
elif self.method == "ecc":
return self.applyEcc(raw_frame)
return self.apply_ecc(raw_frame)
elif self.method == "sparseOptFlow":
return self.applySparseOptFlow(raw_frame)
return self.apply_sparseoptflow(raw_frame)
else:
return np.eye(2, 3)
def applyEcc(self, raw_frame: np.array) -> np.array:
def apply_ecc(self, raw_frame: np.array) -> np.array:
"""
Apply the ECC (Enhanced Correlation Coefficient) algorithm to a raw frame for motion compensation.
@ -128,7 +128,7 @@ class GMC:
Examples:
>>> gmc = GMC(method="ecc")
>>> processed_frame = gmc.applyEcc(np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]))
>>> processed_frame = gmc.apply_ecc(np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]))
>>> print(processed_frame)
[[1. 0. 0.]
[0. 1. 0.]]
@ -161,7 +161,7 @@ class GMC:
return H
def applyFeatures(self, raw_frame: np.array, detections: list = None) -> np.array:
def apply_features(self, raw_frame: np.array, detections: list = None) -> np.array:
"""
Apply feature-based methods like ORB or SIFT to a raw frame.
@ -175,7 +175,7 @@ class GMC:
Examples:
>>> gmc = GMC(method="orb")
>>> raw_frame = np.random.randint(0, 255, (480, 640, 3), dtype=np.uint8)
>>> processed_frame = gmc.applyFeatures(raw_frame)
>>> processed_frame = gmc.apply_features(raw_frame)
>>> print(processed_frame.shape)
(2, 3)
"""
@ -304,7 +304,7 @@ class GMC:
return H
def applySparseOptFlow(self, raw_frame: np.array) -> np.array:
def apply_sparseoptflow(self, raw_frame: np.array) -> np.array:
"""
Apply Sparse Optical Flow method to a raw frame.
@ -316,7 +316,7 @@ class GMC:
Examples:
>>> gmc = GMC()
>>> result = gmc.applySparseOptFlow(np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]))
>>> result = gmc.apply_sparseoptflow(np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]))
>>> print(result)
[[1. 0. 0.]
[0. 1. 0.]]