update sim

.gitignore

@@ -1,2 +1,3 @@
 __pycache__
 .idea
+*.DS_Store

README.md

@@ -11,11 +11,12 @@ If you have any questions or suggestions, you can reach us through:
 - Email: tototianhao@gmail.com
 - telegram: https://t.me/+JoFE2vqHU4phZjg1
 - QQ Group: 10419777
-- WeChat Group: <img src="./images/wechat.jpg" width="200">
+- WeChat Group: <img src="./images/wechat.jpg" width="300">
 
 ## V1.2.0 Update
 1. Add PM_SuperColorTransfer node to simplify the color transfer process
 2. Add PM_SuperMakeUpTransfer node to simplify the process of makeup transfer 
+3. Add v1.2.0 workflow
 
 
 ## V1.1.0 Update
@@ -131,6 +132,8 @@ Click "Load" in the right panel of ComfyUI and select the ./workflow/easyphoto_w
 * Face Shape Match PM: Apply a certain level of fusion between the diffused image and the original image to reduce differences around the face.
 
 * Makeup Transfer PM: Use a GAN network model to perform makeup transfer.
+* SuperMakeUpTransfer PM:(Multi-node integration) makeup by merging two pictures
+* SuperColorTransfer PM：(Multi-node integration) transfer the colors of two pictures
 ## Contribution
 
 If you find any issues or have suggestions for improvement, feel free to contribute. Follow these steps:

README_zh-CN.md

@@ -13,11 +13,12 @@ English | [简体中文](./README_zh-CN.md)
 - 电子邮件：tototianhao@gmail.com
 - telegram: https://t.me/+JoFE2vqHU4phZjg1
 - QQ 群：10419777
-- 微信群： <img src="./images/wechat.jpg" width="200">
+- 微信群： <img src="./images/wechat.jpg" width="300">
 
 ## V1.2.0 Update
 1. 增加PM_SuperColorTransfer 节点，简化了颜色迁移的流程
 2. 增加PM_SuperMakeUpTransfer 节点，简化了进行装扮迁移的流程
+3. 增加v1.2.0 workflow 
 
 ## v1.1.0 更新
 1. faceskin 增加模糊选项
@@ -117,6 +118,8 @@ Easyphoto工作位置: [./workflow/easyphoto.json](./workflows/easyphoto.json )
 * GetImageInfo PM: 提取图片的宽高
 * FaceShapMatchPM: 扩散后的图片和原图片进行一定的融合，减少脸旁边的差异
 * MakeUpTransferPM: 使用gan网络模型对妆容进行一定的迁移
+* SuperMakeUpTransferPM:(多节点的整合)融合两张图片的装扮
+* SuperColorTransferPM：(多节点的整合)迁移两张图片的颜色
 
 ## 贡献
 

__init__.py

@@ -1,12 +1,9 @@
-import sys
-import os
+import os, sys
 
 main_path = os.path.dirname(__file__)
 sys.path.append(main_path)
 
-import subprocess
-import threading
-
+import portrait.install
 import requests
 from tqdm import tqdm
 from portrait.nodes import *
@@ -14,30 +11,6 @@ from portrait.nodes import *
 # import pydevd_pycharm
 # pydevd_pycharm.settrace('49.7.62.197', port=10090, stdoutToServer=True, stderrToServer=True)
 
-
-def handle_stream(stream, prefix):
-    for line in stream:
-        print(prefix, line, end="")
-
-def run_script(cmd, cwd='.'):
-    process = subprocess.Popen(cmd, cwd=cwd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, bufsize=1)
-
-    stdout_thread = threading.Thread(target=handle_stream, args=(process.stdout, ""))
-    stderr_thread = threading.Thread(target=handle_stream, args=(process.stderr, "[!]"))
-
-    stdout_thread.start()
-    stderr_thread.start()
-
-    stdout_thread.join()
-    stderr_thread.join()
-
-    return process.wait()
-
-print("##  installing dependencies")
-
-requirements_path = os.path.join(main_path, "requirements.txt")
-run_script([sys.executable, '-s', '-m', 'pip', 'install', '-q', '-r', requirements_path])
-
 def urldownload_progressbar(url, file_path):
     response = requests.get(url, stream=True)
     total_size = int(response.headers.get('content-length', 0))
@@ -79,6 +52,7 @@ NODE_CLASS_MAPPINGS = {
     "PM_FaceShapMatch": FaceShapMatchPM,
     "PM_SuperColorTransfer": SuperColorTransferPM,
     "PM_SuperMakeUpTransfer": SuperMakeUpTransferPM,
+    "PM_Similarity": SimilarityPM,
 }
 NODE_DISPLAY_NAME_MAPPINGS = {
     "PM_RetinaFace": "RetinaFace PM",
@@ -100,6 +74,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "PM_FaceShapMatch": "FaceShapMatch PM",
     "PM_SuperColorTransfer": "SuperColorTransfer PM",
     "PM_SuperMakeUpTransfer": "SuperMakeUpTransfer PM",
+    "PM_Similarity": "Similarity PM",
+
 }
 
 __all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS']

portrait/config.py

@@ -6,7 +6,7 @@ utils_path = os.path.join(root_path, "utils")
 models_path = os.path.join(root_path, "models")
 # save_dirs
 urls = [
-    "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/webui/ChilloutMix-ni-fp16.safetensors",
+    # "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/webui/ChilloutMix-ni-fp16.safetensors",
     "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/webui/control_v11p_sd15_openpose.pth",
     "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/webui/control_v11p_sd15_canny.pth",
     "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/webui/control_v11f1e_sd15_tile.pth",
@@ -23,7 +23,7 @@ urls = [
 
 ]
 filenames = [
-    os.path.join(folder_names_and_paths['checkpoints'][0][0], "Chilloutmix-Ni-pruned-fp16-fix.safetensors"),
+    # os.path.join(folder_names_and_paths['checkpoints'][0][0], "Chilloutmix-Ni-pruned-fp16-fix.safetensors"),
     os.path.join(folder_names_and_paths['controlnet'][0][0], "control_v11p_sd15_openpose.pth"),
     os.path.join(folder_names_and_paths['controlnet'][0][0], "control_v11p_sd15_canny.pth"),
     os.path.join(folder_names_and_paths['controlnet'][0][0], "control_v11f1e_sd15_tile.pth"),

portrait/install.py

@@ -0,0 +1,107 @@
+import sys
+import subprocess
+import threading
+import locale
+import traceback
+import re
+from portrait.config import *
+
+windows_not_install = ['mmcv_full\n']
+
+def log(msg, end=None, file=None):
+    print('Portrait Maker ==============', msg, end=end, file=file)
+
+def handle_stream(stream, is_stdout):
+    stream.reconfigure(encoding=locale.getpreferredencoding(), errors='replace')
+
+    for msg in stream:
+        if is_stdout:
+            log(msg, end="", file=sys.stdout)
+        else:
+            log(msg, end="", file=sys.stderr)
+
+def process_wrap(cmd_str, cwd=None, handler=None):
+    log(f"[Portrait Maker] EXECUTE: {cmd_str} in '{cwd}'")
+    process = subprocess.Popen(cmd_str, cwd=cwd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True, bufsize=1)
+
+    if handler is None:
+        handler = handle_stream
+
+    stdout_thread = threading.Thread(target=handler, args=(process.stdout, True))
+    stderr_thread = threading.Thread(target=handler, args=(process.stderr, False))
+
+    stdout_thread.start()
+    stderr_thread.start()
+
+    stdout_thread.join()
+    stderr_thread.join()
+
+    return process.wait()
+
+# ---
+pip_list = None
+
+def get_installed_packages():
+    global pip_list
+    if pip_list is None:
+        try:
+            result = subprocess.check_output([sys.executable, '-m', 'pip', 'list'], universal_newlines=True)
+            pip_list = set([line.split()[0].lower() for line in result.split('\n') if line.strip()])
+        except subprocess.CalledProcessError as e:
+            log(f"[ComfyUI-Manager] Failed to retrieve the information of installed pip packages.")
+            return set()
+
+    return pip_list
+
+def is_installed(name):
+    name = name.strip()
+    pattern = r'([^<>!=]+)([<>!=]=?)'
+    match = re.search(pattern, name)
+
+    if match:
+        name = match.group(1)
+
+    result = name.lower() in get_installed_packages()
+    return result
+
+def check_and_install_requirements(file_path):
+    log(file_path)
+    version = sys.version_info[:2]
+    if os.path.exists(file_path):
+        with open(file_path, 'r') as file:
+            lines = file.readlines()
+            for line in lines:
+                log(line)
+                if not is_installed(line):
+                    if platform.system() == "Windows" and version[1] == 11 and 'insightface' in line:
+                        process_wrap(pip_install + ['insightface-0.7.3-cp311-cp311-win_amd64.whl'], cwd=root_path)
+                        continue
+                    if platform.system() == "Windows" and line in windows_not_install:
+                        log(f"windows skip {line}")
+                        continue
+                    log(f"install {line}")
+                    process_wrap(pip_install + [line], cwd=root_path)
+            return False
+    return True
+
+try:
+    import platform
+
+    log("### ComfyUI-Portrait-Maker: Check dependencies")
+    if "python_embed" in sys.executable or "python_embedded" in sys.executable:
+        pip_install = [sys.executable, '-s', '-m', 'pip', 'install', '-q']
+        mim_install = [sys.executable, '-s', '-m', 'mim', 'install']
+    else:
+        pip_install = [sys.executable, '-m', 'pip', 'install', '-q']
+        mim_install = [sys.executable, '-m', 'mim', 'install']
+
+    subpack_req = os.path.join(root_path, "requirements.txt")
+    check_and_install_requirements(subpack_req)
+    if platform.system() != "Windows" :
+        process_wrap(pip_install + ['mmcv_full'], cwd=root_path)
+    if sys.argv[0] == 'install.py':
+        sys.path.append('.')  # for portable version
+
+except Exception as e:
+    log("[ERROR] ComfyUI-Impact-Pack: Dependency installation has failed. Please install manually.")
+    traceback.print_exc()

portrait/model_holder.py

@@ -16,6 +16,7 @@ skin_retouching = None
 portrait_enhancement = None
 psgan_interface = None
 real_gan_sr = None
+face_recognition = None
 
 def get_retinaface_detection():
     global retinaface_detection
@@ -72,3 +73,10 @@ def get_pagan_interface():
         makeup_transfer_model_path = os.path.join(models_path, "makeup_transfer.pth")
         psgan_interface = PSGAN_Inference("cuda", makeup_transfer_model_path, get_retinaface_detection(), get_face_skin(), face_landmarks_model_path)
     return psgan_interface
+
+def get_face_recognition():
+    global face_recognition
+    if face_recognition is None:
+        face_recognition = pipeline("face_recognition", model="bubbliiiing/cv_retinafce_recognition", model_revision="v1.0.3")
+    return face_recognition
+

portrait/nodes.py

@@ -6,9 +6,9 @@ from .utils.face_process_utils import call_face_crop, color_transfer, Face_Skin
 from .utils.img_utils import img_to_tensor, tensor_to_img, tensor_to_np, np_to_tensor, np_to_mask, img_to_mask, img_to_np
 from .model_holder import *
 
-import pydevd_pycharm
-
-pydevd_pycharm.settrace('49.7.62.197', port=10090, stdoutToServer=True, stderrToServer=True)
+# import pydevd_pycharm
+#
+# pydevd_pycharm.settrace('49.7.62.197', port=10090, stdoutToServer=True, stderrToServer=True)
 
 class RetinaFacePM:
     @classmethod
@@ -46,6 +46,14 @@ class FaceFusionPM:
 
     CATEGORY = "protrait/model"
 
+    def resize(self, tensor):
+        image = tensor_to_img(tensor)
+        short_side = max(image.width, image.height)
+        resize = float(short_side / 640)
+        new_size = (int(image.width // resize), int(image.height // resize))
+        resize_image = image.resize(new_size, Image.Resampling.LANCZOS)
+        return img_to_np(resize_image)
+
     def img_face_fusion(self, source_image, swap_image, mode):
         if mode == "ali":
             source_image = tensor_to_img(source_image)
@@ -55,12 +63,24 @@ class FaceFusionPM:
             result_image = Image.fromarray(cv2.cvtColor(fusion_image, cv2.COLOR_BGR2RGB))
             return (img_to_tensor(result_image),)
         else:
+            width, height = source_image.shape[2], source_image.shape[1]
+            need_resize = False
+            source_np = tensor_to_np(source_image)
+            swap_np = tensor_to_np(swap_image)
+            if source_image.shape[2] > 640 or source_image.shape[1] > 640:
+                source_np = self.resize(source_image)
+                need_resize = True
+            if swap_image.shape[2] > 640 or swap_image.shape[1] > 640:
+                swap_np = self.resize(swap_image)
             get_face_analysis().prepare(ctx_id=0, det_size=(640, 640))
-            source_image = tensor_to_np(source_image)
-            faces = get_face_analysis().get(source_image)
-            swap_image = tensor_to_np(swap_image)
-            swap_face = get_face_analysis().get(swap_image)
-            result_image = get_roop().get(source_image, faces[0], swap_face[0], paste_back=True)
+            faces = get_face_analysis().get(source_np)
+            swap_faces = get_face_analysis().get(swap_np)
+            result_image = get_roop().get(source_np, faces[0], swap_faces[0], paste_back=True)
+            if need_resize:
+                image = Image.fromarray(result_image)
+                new_size = width, height
+                result_image = image.resize(new_size, Image.Resampling.LANCZOS)
+                result_image = img_to_np(result_image)
             return (np_to_tensor(result_image),)
 
 class RatioMerge2ImagePM:
@@ -77,7 +97,7 @@ class RatioMerge2ImagePM:
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "image_ratio_merge"
 
-    CATEGORY = "protrait/model"
+    CATEGORY = "protrait/other"
 
     def image_ratio_merge(self, image1, image2, fusion_rate):
         rate_fusion_image = image1 * (1 - fusion_rate) + image2 * fusion_rate
@@ -136,7 +156,7 @@ class ExpandMaskFaceWidthPM:
     RETURN_TYPES = ("MASK", "BOX")
     FUNCTION = "expand_mask_face_width"
 
-    CATEGORY = "protrait/model"
+    CATEGORY = "protrait/other"
 
     def expand_mask_face_width(self, mask, box, expand_width):
         h, w = mask.shape[1], mask.shape[2]
@@ -164,7 +184,7 @@ class BoxCropImagePM:
     RETURN_TYPES = ("IMAGE",)
     RETURN_NAMES = ("crop_image",)
     FUNCTION = "box_crop_image"
-    CATEGORY = "protrait/model"
+    CATEGORY = "protrait/other"
 
     def box_crop_image(self, image, box):
         image = image[:, box[1]:box[3], box[0]:box[2], :]
@@ -182,7 +202,7 @@ class ColorTransferPM:
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "color_transfer"
 
-    CATEGORY = "protrait/model"
+    CATEGORY = "protrait/other"
 
     def color_transfer(self, transfer_from, transfer_to):
         transfer_result = color_transfer(tensor_to_np(transfer_from), tensor_to_np(transfer_to))  # 进行颜色迁移
@@ -223,7 +243,7 @@ class MaskDilateErodePM:
     RETURN_TYPES = ("MASK",)
     FUNCTION = "mask_dilate_erode"
 
-    CATEGORY = "protrait/model"
+    CATEGORY = "protrait/other"
 
     def mask_dilate_erode(self, mask):
         out_mask = Image.fromarray(np.uint8(cv2.dilate(tensor_to_np(mask), np.ones((96, 96), np.uint8), iterations=1) - cv2.erode(tensor_to_np(mask), np.ones((48, 48), np.uint8), iterations=1)))
@@ -275,13 +295,13 @@ class ImageScaleShortPM:
         return {"required": {
             "image": ("IMAGE",),
             "size": ("INT", {"default": 512, "min": 0, "max": 2048, "step": 1}),
-            "crop_face": ("BOOLEAN", {"default": False, "label_on": "enabled", "label_off": "disabled"}),
+            "crop_face": ("BOOLEAN", {"default": False}),
         }}
 
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "image_scale_short"
 
-    CATEGORY = "protrait/model"
+    CATEGORY = "protrait/other"
 
     def image_scale_short(self, image, size, crop_face):
         input_image = tensor_to_img(image)
@@ -308,7 +328,7 @@ class ImageResizeTargetPM:
 
     FUNCTION = "image_resize_target"
 
-    CATEGORY = "protrait/model"
+    CATEGORY = "protrait/other"
 
     def image_resize_target(self, image, width, height):
         imagepi = tensor_to_img(image)
@@ -327,7 +347,7 @@ class GetImageInfoPM:
 
     FUNCTION = "get_image_info"
 
-    CATEGORY = "protrait/model"
+    CATEGORY = "protrait/other"
 
     def get_image_info(self, image):
         width = image.shape[2]
@@ -349,6 +369,8 @@ class MakeUpTransferPM:
     CATEGORY = "protrait/model"
 
     def makeup_transfer(self, source_image, makeup_image):
+        source_image = tensor_to_img(source_image)
+        makeup_image = tensor_to_img(makeup_image)
         result = get_pagan_interface().transfer(source_image, makeup_image)
         return (img_to_tensor(result),)
 
@@ -407,10 +429,11 @@ class SuperColorTransferPM:
     RETURN_TYPES = ("IMAGE",)
 
     FUNCTION = "super_color_transfer"
-    CATEGORY = "protrait/model"
+    CATEGORY = "protrait/super"
 
     def super_color_transfer(self, main_image, transfer_image, avatar_box=None):
         origin_np = tensor_to_np(main_image)
+        result_np = None
         if avatar_box is not None:
             main_image = main_image[:, avatar_box[1]:avatar_box[3], avatar_box[0]:avatar_box[2], :]
             transfer_image = transfer_image[:, avatar_box[1]:avatar_box[3], avatar_box[0]:avatar_box[2], :]
@@ -422,10 +445,13 @@ class SuperColorTransferPM:
         face_skin_np = cv2.blur(face_skin_np, (32, 32)) / 255
 
         masked_img_np = tensor_to_np(main_image) * (1 - face_skin_np) + transfer_result * face_skin_np
+        result_np = masked_img_np
 
-        origin_np[avatar_box[1]:avatar_box[3], avatar_box[0]:avatar_box[2], :] = masked_img_np
+        if avatar_box is not None:
+            origin_np[avatar_box[1]:avatar_box[3], avatar_box[0]:avatar_box[2], :] = masked_img_np
+            result_np = origin_np
 
-        return (np_to_tensor(origin_np),)
+        return (np_to_tensor(result_np),)
 
 class SuperMakeUpTransferPM:
 
@@ -444,7 +470,7 @@ class SuperMakeUpTransferPM:
 
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "super_makeup_transfer"
-    CATEGORY = "protrait/model"
+    CATEGORY = "protrait/super"
 
     def super_makeup_transfer(self, main_image, makeup_image, avatar_box=None):
         box_width, box_height = avatar_box[2] - avatar_box[0], avatar_box[3] - avatar_box[1]
@@ -458,3 +484,36 @@ class SuperMakeUpTransferPM:
         box_size_transfer = transfer_image.resize([box_width, box_height], Image.Resampling.LANCZOS)
         origin_np[avatar_box[1]:avatar_box[3], avatar_box[0]:avatar_box[2], :] = img_to_np(box_size_transfer)
         return (np_to_tensor(origin_np),)
+
+class SimilarityPM:
+    @classmethod
+    def INPUT_TYPES(s):
+        return \
+            {
+                "required": {
+                    "main_image": ("IMAGE",),
+                    "compare_image": ("IMAGE",),
+                    "model": (["sim"],),
+                    "result_prefix": ("STRING",{"default": ""}),
+                },
+            }
+
+    RETURN_TYPES = ("STRING",)
+
+    FUNCTION = "similarity_compare"
+    CATEGORY = "protrait/model"
+
+    def similarity_compare(self, main_image, compare_image, model, result_prefix):
+        main_image_copy = tensor_to_img(main_image)
+        compare_image_copy = tensor_to_img(compare_image)
+        score = None
+        result = None
+        if model == "sim":
+            root_embedding = get_face_recognition()(dict(user=Image.fromarray(np.uint8(main_image_copy))))[OutputKeys.IMG_EMBEDDING]
+            compare_embedding = get_face_recognition()(dict(user=Image.fromarray(np.uint8(compare_image_copy))))[OutputKeys.IMG_EMBEDDING]
+            score = float(np.dot(root_embedding, np.transpose(compare_embedding))[0][0])
+        if result_prefix is "":
+            result = str(round(score, 2))
+        else:
+            result = f"{result_prefix}_{round(score, 2)}"
+        return (result,)

portrait/utils/psgan_utils.py

@@ -456,7 +456,7 @@ class PreProcess:
         lms = lms[:, ::-1]
 
         mask, diff = self.process(mask, lms, device=self.device)
-        image = image.resize((self.img_size, self.img_size), Image.ANTIALIAS)
+        image = image.resize((self.img_size, self.img_size), Image.Resampling.NEAREST)
         image = self.transform(image)
         real = to_var(image.unsqueeze(0))
         return [real, mask, diff], face_on_image, crop_face
@@ -830,7 +830,7 @@ class PostProcess:
 
         height, width = source.shape[:2]
         small_source = cv2.resize(source, (self.img_size, self.img_size))
-        laplacian_diff = source.astype(np.float) - cv2.resize(small_source, (width, height)).astype(np.float)
+        laplacian_diff = source.astype(np.float64) - cv2.resize(small_source, (width, height)).astype(np.float64)
         result = (cv2.resize(result, (width, height)) + laplacian_diff).round().clip(0, 255).astype(np.uint8)
         if self.denoise:
             result = cv2.fastNlMeansDenoisingColored(result)

requirements.txt

@@ -1,3 +1,4 @@
+aliyun-python-sdk-core-v3==2.13.10
 opencv-python
 tensorflow-cpu
 tensorflow
@@ -7,4 +8,5 @@ modelscope
 scikit-image
 matplotlib
 insightface
-diffusers==0.18.2
+diffusers==0.18.2
+sentencepiece