nodes/hughescr-ComfyUI-OpenPose-Keypoint-Extractor
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Merge pull request #6 from andypotato/feat/min-confidence

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Feature: Add minimum confidence for keypoints
This commit is contained in:
Craig Hughes
2025-07-30 08:44:50 -07:00
committed by GitHub
parent 61ac9d9e6a 370f4161e3
commit d434cecedf
1 changed files with 23 additions and 10 deletions
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openpose_keypoint_extractor.py
+23 -10
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@@ -1,4 +1,3 @@
import json
from nodes import MAX_RESOLUTION
class OpenPoseKeyPointExtractor:
@@ -10,6 +9,7 @@ class OpenPoseKeyPointExtractor:
"image_width": ("INT", { "min": 0, "max": MAX_RESOLUTION }),
"image_height": ("INT", { "min": 0, "max": MAX_RESOLUTION }),
"points_list": ("STRING", {"multiline": True, "default": ""}),
"min_confidence": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
},
"optional": {
"person_number": ("INT", { "default": 0 }),
@@ -25,25 +25,38 @@ class OpenPoseKeyPointExtractor:
idx_x = item*3
idx_y = idx_x + 1
idx_conf = idx_y + 1
# prevent out of bounds errors
if idx_conf >= len(list):
return (0.0, 0.0, 0.0)
return (list[idx_x], list[idx_y], list[idx_conf])
def box_keypoints(self, pose_keypoint, image_width, image_height, points_list, person_number=0):
def box_keypoints(self, pose_keypoint, image_width, image_height, points_list,
person_number=0, min_confidence=0.5):
points_we_want = [int(element) for element in points_list.split(",")]
min_x = MAX_RESOLUTION
min_y = MAX_RESOLUTION
max_x = 0
max_y = 0
for element in points_we_want:
(x,y,z) = self.get_keypoint_from_list(pose_keypoint[0]["people"][person_number]["pose_keypoints_2d"], element)
if x < min_x:
min_x = x
if y < min_y:
min_y = y
if x > max_x:
max_x = x
if y > max_y:
max_y = y
# only include points that meet the minimum confidence
if z >= min_confidence:
if x < min_x:
min_x = x
if y < min_y:
min_y = y
if x > max_x:
max_x = x
if y > max_y:
max_y = y
# in case no valid keypoints were found return the full image
if min_x == MAX_RESOLUTION:
return (0, 0, image_width, image_height)
return (int(min_x*image_width), int(min_y*image_height), int((max_x-min_x)*image_width), int((max_y-min_y)*image_height))
NODE_CLASS_MAPPINGS = {