diff --git a/README.md b/README.md
index 2f3b4ea..7dc437b 100644
--- a/README.md
+++ b/README.md
@@ -1,2 +1,35 @@
-# comfyui-openpose-render
-ultimate node for openpose rendering
+
+
+# ComfyUI ultimate openpose render
+
+
+
+
+ 
+
+
+This is a better version of openpose pose render in ComfyUI with both pose keypoints and pose json input options. It also gives the plotting controls with canvas size and pose marker size.
+
+If you like the project, please give me a star! ⭐
+
+## Installation
+
+- Just install this repo through the Manager. Or you can manually install it, go to ComfyUI `/custom_nodes` directory
+ ```bash
+ git clone https://github.com/westNeighbor/ComfyUI-ultimate-openpose-render
+ cd ./ComfyUI-ultimate-openpose-render
+ pip install -r requirements.txt # if you use portable version, see below
+ ```
+ if you use portable version, install requirement accordingly, for example, I have portable in my E: disk
+ ```bash
+ E:/ComfyUI_windows_portable/python_embeded/python.exe -m pip install -r requirements.txt
+ ```
+## Usage
+- Insert node by `Right Click -> ultimate-openpose -> Openpose Render Node`
+
+## Features
+- Accept both pose keypoints and pose json format input. Be ware that the edit priority is **POSE\_KEYPOINT > POSE\_JSON**
+
+- Can adjust output canvas size
+
+- Can control the pose marker size
diff --git a/__init__.py b/__init__.py
new file mode 100644
index 0000000..df9ff70
--- /dev/null
+++ b/__init__.py
@@ -0,0 +1,12 @@
+from .openpose_render_nodes import OpenposeRenderNode
+
+
+NODE_CLASS_MAPPINGS = {
+ "OpenposeRenderNode": OpenposeRenderNode,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+ "OpenposeRenderNode": "Openpose Render Node",
+}
+
+__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]
diff --git a/assets/render_example.png b/assets/render_example.png
new file mode 100644
index 0000000..ab78670
Binary files /dev/null and b/assets/render_example.png differ
diff --git a/openpose_render_nodes.py b/openpose_render_nodes.py
new file mode 100644
index 0000000..768e3cb
--- /dev/null
+++ b/openpose_render_nodes.py
@@ -0,0 +1,54 @@
+import json
+import numpy as np
+import torch
+from .util import draw_pose, draw_pose_json
+
+class OpenposeRenderNode:
+ @classmethod
+ def INPUT_TYPES(s):
+ return {
+ "optional": {
+ "show_body": ("BOOLEAN", {"default": True}),
+ "show_face": ("BOOLEAN", {"default": True}),
+ "show_hands": ("BOOLEAN", {"default": True}),
+ "resolution_x": ("INT", {
+ "default": -1,
+ "min": -1,
+ "max": 12800
+ }),
+ "pose_marker_size": ("INT", {
+ "default": 4,
+ "min": 0,
+ "max": 100
+ }),
+ "face_marker_size": ("INT", {
+ "default": 3,
+ "min": 0,
+ "max": 100
+ }),
+ "hand_marker_size": ("INT", {
+ "default": 2,
+ "min": 0,
+ "max": 100
+ }),
+ "POSE_JSON": ("STRING", {"multiline": True}),
+ "POSE_KEYPOINT": ("POSE_KEYPOINT",{"default": None}),
+ },
+ }
+
+ RETURN_TYPES = ("IMAGE",)
+ FUNCTION = "render_img"
+ CATEGORY = "ultimate-openpose"
+
+ def render_img(self, show_body, show_face, show_hands, resolution_x, pose_marker_size, face_marker_size, hand_marker_size, POSE_JSON, POSE_KEYPOINT=None):
+ if POSE_KEYPOINT is not None:
+ POSE_JSON = json.dumps(POSE_KEYPOINT).replace("'",'"').replace('None','[]')
+ elif POSE_JSON:
+ POSE_JSON = POSE_JSON.replace("'",'"').replace('None','[]')
+
+ pose_imgs = draw_pose_json(POSE_JSON, resolution_x, show_body, show_face, show_hands, pose_marker_size, face_marker_size, hand_marker_size)
+ if pose_imgs:
+ pose_imgs_np = np.array(pose_imgs).astype(np.float32) / 255
+ return (torch.from_numpy(pose_imgs_np),)
+ else:
+ raise ValueError("Invalid input type. Expected an input to give an output.")
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..1e803d2
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,14 @@
+[project]
+name = "ComfyUI-ultimate-openpose-render"
+description = "The ultimate openpose render node for ComfyUI with flexible input, output and adjustment."
+version = "1.0"
+license = "LICENSE"
+
+[project.urls]
+Repository = "https://github.com/westNeighbor/ComfyUI-openpose-render"
+# Used by Comfy Registry https://comfyregistry.org
+
+[tool.comfy]
+PublisherId = "westNeighbor"
+DisplayName = "ComfyUI-ultimate-openpose-render"
+Icon = ""
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..a4af5da
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,5 @@
+polygraphy
+matplotlib
+numpy
+cv2
+torch
diff --git a/util.py b/util.py
new file mode 100644
index 0000000..795b118
--- /dev/null
+++ b/util.py
@@ -0,0 +1,191 @@
+import math
+import json
+import numpy as np
+import matplotlib
+import cv2
+from comfy.utils import ProgressBar
+
+eps = 0.01
+
+def draw_pose_json(pose_json, resolution_x, show_body, show_face, show_hands, pose_marker_size, face_marker_size, hand_marker_size):
+ pose_imgs = []
+ if pose_json:
+ if pose_json.startswith('{'):
+ pose_json = '[{}]'.format(pose_json)
+ images = json.loads(pose_json)
+ pbar = ProgressBar(len(images))
+ for image in images:
+ if 'people' not in image:
+ pbar.update(len(images))
+ return pose_imgs
+ figures = image['people']
+ H = image['canvas_height']
+ W = image['canvas_width']
+ bodies = []
+ candidate = []
+ subset = [[]]
+ faces = []
+ hands = []
+ for figure in figures:
+ if 'pose_keypoints_2d' in figure:
+ body = figure['pose_keypoints_2d']
+ if 'face_keypoints_2d' in figure:
+ face = figure['face_keypoints_2d']
+ if 'hand_left_keypoints_2d' in figure:
+ lhand = figure['hand_left_keypoints_2d']
+ if 'hand_right_keypoints_2d' in figure:
+ rhand = figure['hand_right_keypoints_2d']
+ if body:
+ for i in range(0,len(body),3):
+ candidate.append(body[i:i+2])
+ if not subset[0]:
+ subset[0].extend([len(subset[0])+(i//3) if body[i+2]>0 else -1 for i in range(0,len(body),3)])
+ else:
+ subset.append([len(subset[0])*len(subset)+(i//3) if body[i+2]>0 else -1 for i in range(0,len(body),3)])
+ if face:
+ faces.append([face[i:i+2] for i in range(0,len(face),3)])
+ if lhand:
+ hands.append([lhand[i:i+2] for i in range(0,len(lhand),3)])
+ if rhand:
+ hands.append([rhand[i:i+2] for i in range(0,len(rhand),3)])
+
+ normalized = 0.0
+ if candidate:
+ candidate = np.array(candidate).astype(float)
+ subset = np.array(subset)
+ normalized = max(np.max(candidate[...,0]),np.max(candidate[...,1]))
+ if normalized>2.0:
+ candidate[...,0] /= float(W)
+ candidate[...,1] /= float(H)
+ if faces:
+ faces = np.array(faces).astype(float)
+ normalized = max(np.max(faces[...,0]),np.max(faces[...,1]))
+ if normalized>2.0:
+ faces[...,0] /= float(W)
+ faces[...,1] /= float(H)
+ if hands:
+ hands = np.array(hands).astype(float)
+ normalized = max(np.max(hands[...,0]),np.max(hands[...,1]))
+ if normalized>2.0:
+ hands[...,0] /= float(W)
+ hands[...,1] /= float(H)
+ bodies = dict(candidate=candidate, subset=subset)
+ pose = dict(bodies=bodies, faces=faces, hands=hands)
+ pose = dict(bodies=bodies if show_body else {'candidate':[], 'subset':[]}, faces=faces if show_face else [], hands=hands if show_hands else [])
+ W_scaled = resolution_x
+ if resolution_x < 64:
+ W_scaled = W
+ H_scaled = int(H*(W_scaled*1.0/W))
+ pose_img = draw_pose(pose, H_scaled, W_scaled, pose_marker_size, face_marker_size, hand_marker_size)
+ pose_imgs.append(pose_img)
+ pbar.update(1)
+
+ return pose_imgs
+
+def draw_pose(pose, H, W, pose_marker_size, face_marker_size, hand_marker_size):
+ bodies = pose['bodies']
+ faces = pose['faces']
+ hands = pose['hands']
+ candidate = bodies['candidate']
+ subset = bodies['subset']
+ canvas = np.zeros(shape=(H, W, 3), dtype=np.uint8)
+
+ if len(candidate) > 0:
+ canvas = draw_bodypose(canvas, candidate, subset, pose_marker_size)
+
+ if len(hands) > 0:
+ canvas = draw_handpose(canvas, hands, hand_marker_size)
+
+ if len(faces) > 0:
+ canvas = draw_facepose(canvas, faces, face_marker_size)
+
+ return canvas
+
+def draw_bodypose(canvas, candidate, subset, pose_marker_size):
+ H, W, C = canvas.shape
+ candidate = np.array(candidate)
+ subset = np.array(subset)
+
+ # stickwidth = 4
+
+ limbSeq = [[2, 3], [2, 6], [3, 4], [4, 5], [6, 7], [7, 8], [2, 9], [9, 10], \
+ [10, 11], [2, 12], [12, 13], [13, 14], [2, 1], [1, 15], [15, 17], \
+ [1, 16], [16, 18], [3, 17], [6, 18]]
+
+ colors = [[255, 0, 0], [255, 85, 0], [255, 170, 0], [255, 255, 0], [170, 255, 0], [85, 255, 0], [0, 255, 0], \
+ [0, 255, 85], [0, 255, 170], [0, 255, 255], [0, 170, 255], [0, 85, 255], [0, 0, 255], [85, 0, 255], \
+ [170, 0, 255], [255, 0, 255], [255, 0, 170], [255, 0, 85]]
+
+ for i in range(17):
+ for n in range(len(subset)):
+ index = subset[n][np.array(limbSeq[i]) - 1]
+ if -1 in index:
+ continue
+ Y = candidate[index.astype(int), 0] * float(W)
+ X = candidate[index.astype(int), 1] * float(H)
+ mX = np.mean(X)
+ mY = np.mean(Y)
+ length = ((X[0] - X[1]) ** 2 + (Y[0] - Y[1]) ** 2) ** 0.5
+ angle = math.degrees(math.atan2(X[0] - X[1], Y[0] - Y[1]))
+ polygon = cv2.ellipse2Poly((int(mY), int(mX)), (int(length / 2), pose_marker_size), int(angle), 0, 360, 1)
+ cv2.fillConvexPoly(canvas, polygon, colors[i])
+
+ canvas = (canvas * 0.6).astype(np.uint8)
+
+ for i in range(18):
+ for n in range(len(subset)):
+ index = int(subset[n][i])
+ if index == -1:
+ continue
+ x, y = candidate[index][0:2]
+ x = int(x * W)
+ y = int(y * H)
+ cv2.circle(canvas, (int(x), int(y)), pose_marker_size, colors[i], thickness=-1)
+
+ return canvas
+
+
+def draw_handpose(canvas, all_hand_peaks, hand_marker_size):
+ H, W, C = canvas.shape
+
+ edges = [[0, 1], [1, 2], [2, 3], [3, 4], [0, 5], [5, 6], [6, 7], [7, 8], [0, 9], [9, 10], \
+ [10, 11], [11, 12], [0, 13], [13, 14], [14, 15], [15, 16], [0, 17], [17, 18], [18, 19], [19, 20]]
+
+ for peaks in all_hand_peaks:
+ peaks = np.array(peaks)
+
+ for ie, e in enumerate(edges):
+ x1, y1 = peaks[e[0]]
+ x2, y2 = peaks[e[1]]
+ x1 = int(x1 * W)
+ y1 = int(y1 * H)
+ x2 = int(x2 * W)
+ y2 = int(y2 * H)
+ if x1 > eps and y1 > eps and x2 > eps and y2 > eps:
+ cv2.line(canvas, (x1, y1), (x2, y2), matplotlib.colors.hsv_to_rgb([ie / float(len(edges)), 1.0, 1.0]) * 255, thickness=1 if hand_marker_size == 0 else hand_marker_size)
+
+ joint_size=0
+ if hand_marker_size < 2:
+ joint_size = hand_marker_size + 1
+ else:
+ joint_size = hand_marker_size + 2
+ for i, keyponit in enumerate(peaks):
+ x, y = keyponit
+ x = int(x * W)
+ y = int(y * H)
+ if x > eps and y > eps:
+ cv2.circle(canvas, (x, y), joint_size, (0, 0, 255), thickness=-1)
+ return canvas
+
+
+def draw_facepose(canvas, all_lmks, face_marker_size):
+ H, W, C = canvas.shape
+ for lmks in all_lmks:
+ lmks = np.array(lmks)
+ for lmk in lmks:
+ x, y = lmk
+ x = int(x * W)
+ y = int(y * H)
+ if x > eps and y > eps:
+ cv2.circle(canvas, (x, y), face_marker_size, (255, 255, 255), thickness=-1)
+ return canvas