Ankle/yolov5_birdproject
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Update README.md (#13283)

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* Update README.md

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Auto-format by https://ultralytics.com/actions

---------

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn JocherandUltralyticsAssistant authored and GitHub committed 2024-08-26 02:37:25 +02:00
1 parent 427cfc4f73
commit b40781b3e3
15 files changed
+27 -27
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utils/segment/general.py
+6 -6
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@@ -28,7 +28,7 @@ def process_mask_upsample(protos, masks_in, bboxes, shape):
protos: [mask_dim, mask_h, mask_w]
masks_in: [n, mask_dim], n is number of masks after nms
bboxes: [n, 4], n is number of masks after nms
shape: input_image_size, (h, w)
shape: input_image_size, (h, w).
return: h, w, n
"""
@@ -45,7 +45,7 @@ def process_mask(protos, masks_in, bboxes, shape, upsample=False):
proto_out: [mask_dim, mask_h, mask_w]
out_masks: [n, mask_dim], n is number of masks after nms
bboxes: [n, 4], n is number of masks after nms
shape:input_image_size, (h, w)
shape:input_image_size, (h, w).
return: h, w, n
"""
@@ -71,7 +71,7 @@ def process_mask_native(protos, masks_in, bboxes, shape):
protos: [mask_dim, mask_h, mask_w]
masks_in: [n, mask_dim], n is number of masks after nms
bboxes: [n, 4], n is number of masks after nms
shape: input_image_size, (h, w)
shape: input_image_size, (h, w).
return: h, w, n
"""
@@ -92,7 +92,7 @@ def scale_image(im1_shape, masks, im0_shape, ratio_pad=None):
"""
img1_shape: model input shape, [h, w]
img0_shape: origin pic shape, [h, w, 3]
masks: [h, w, num]
masks: [h, w, num].
"""
# Rescale coordinates (xyxy) from im1_shape to im0_shape
if ratio_pad is None: # calculate from im0_shape
@@ -120,7 +120,7 @@ def mask_iou(mask1, mask2, eps=1e-7):
"""
mask1: [N, n] m1 means number of predicted objects
mask2: [M, n] m2 means number of gt objects
Note: n means image_w x image_h
Note: n means image_w x image_h.
return: masks iou, [N, M]
"""
@@ -133,7 +133,7 @@ def masks_iou(mask1, mask2, eps=1e-7):
"""
mask1: [N, n] m1 means number of predicted objects
mask2: [N, n] m2 means number of gt objects
Note: n means image_w x image_h
Note: n means image_w x image_h.
return: masks iou, (N, )
"""
utils/segment/metrics.py
+3 -3
View File
@@ -127,7 +127,7 @@ class Metric:
return (self.mp, self.mr, self.map50, self.map)
def class_result(self, i):
"""Class-aware result, return p[i], r[i], ap50[i], ap[i]"""
"""Class-aware result, return p[i], r[i], ap50[i], ap[i]."""
return (self.p[i], self.r[i], self.ap50[i], self.ap[i])
def get_maps(self, nc):
@@ -140,7 +140,7 @@ class Metric:
def update(self, results):
"""
Args:
results: tuple(p, r, ap, f1, ap_class)
results: tuple(p, r, ap, f1, ap_class).
"""
p, r, all_ap, f1, ap_class_index = results
self.p = p
@@ -163,7 +163,7 @@ class Metrics:
def update(self, results):
"""
Args:
results: Dict{'boxes': Dict{}, 'masks': Dict{}}
results: Dict{'boxes': Dict{}, 'masks': Dict{}}.
"""
self.metric_box.update(list(results["boxes"].values()))
self.metric_mask.update(list(results["masks"].values()))