65 lines
2.3 KiB
Python
65 lines
2.3 KiB
Python
from nodes import MAX_RESOLUTION
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class OpenPoseKeyPointExtractor:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"pose_keypoint": ("POSE_KEYPOINT",),
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"image_width": ("INT", { "min": 0, "max": MAX_RESOLUTION }),
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"image_height": ("INT", { "min": 0, "max": MAX_RESOLUTION }),
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"points_list": ("STRING", {"multiline": True, "default": ""}),
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"min_confidence": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
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},
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"optional": {
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"person_number": ("INT", { "default": 0 }),
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}
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}
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RETURN_TYPES = ("INT", "INT", "INT", "INT")
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RETURN_NAMES = ("x", "y", "width", "height")
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FUNCTION = "box_keypoints"
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CATEGORY = "utils"
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def get_keypoint_from_list(self, list, item):
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idx_x = item*3
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idx_y = idx_x + 1
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idx_conf = idx_y + 1
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# prevent out of bounds errors
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if idx_conf >= len(list):
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return (0.0, 0.0, 0.0)
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return (list[idx_x], list[idx_y], list[idx_conf])
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def box_keypoints(self, pose_keypoint, image_width, image_height, points_list,
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person_number=0, min_confidence=0.5):
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points_we_want = [int(element) for element in points_list.split(",")]
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min_x = MAX_RESOLUTION
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min_y = MAX_RESOLUTION
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max_x = 0
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max_y = 0
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for element in points_we_want:
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(x,y,z) = self.get_keypoint_from_list(pose_keypoint[0]["people"][person_number]["pose_keypoints_2d"], element)
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# only include points that meet the minimum confidence
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if z >= min_confidence:
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if x < min_x:
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min_x = x
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if y < min_y:
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min_y = y
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if x > max_x:
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max_x = x
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if y > max_y:
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max_y = y
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# in case no valid keypoints were found return the full image
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if min_x == MAX_RESOLUTION:
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return (0, 0, image_width, image_height)
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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))
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NODE_CLASS_MAPPINGS = {
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"Openpose Keypoint Extractor": OpenPoseKeyPointExtractor,
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}
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