optimize: import pipeline ondemand

fix: force cpu device for `tensor_paste`
- prevent device mismatch error

modules/impact/config.py

@@ -2,7 +2,7 @@ import configparser
 import os
 
 
-version = "V4.48.3"
+version = "V4.48.4"
 
 dependency_version = 19
 

modules/impact/core.py

@@ -15,12 +15,13 @@ import comfy
 import impact.wildcards as wildcards
 import math
 import cv2
+import time
 
 SEG = namedtuple("SEG",
                  ['cropped_image', 'cropped_mask', 'confidence', 'crop_region', 'bbox', 'label', 'control_net_wrapper'],
                  defaults=[None])
 
-pb_id_cnt = 0
+pb_id_cnt = time.time()
 preview_bridge_image_id_map = {}
 preview_bridge_image_name_map = {}
 preview_bridge_cache = {}

modules/impact/hf_nodes.py

@@ -1,4 +1,3 @@
-from transformers import pipeline
 import comfy
 import re
 from impact.utils import *
@@ -31,6 +30,8 @@ class HF_TransformersClassifierProvider:
     CATEGORY = "ImpactPack/HuggingFace"
 
     def doit(self, preset_repo_id, manual_repo_id, device_mode):
+        from transformers import pipeline
+
         if preset_repo_id == 'Manual repo id':
             url = manual_repo_id
         else:

modules/impact/impact_pack.py

@@ -237,6 +237,8 @@ class DetailerForEach:
             if not (enhanced_image is None):
                 # don't latent composite-> converting to latent caused poor quality
                 # use image paste
+                image = image.cpu()
+                enhanced_image = enhanced_image.cpu()
                 tensor_paste(image, enhanced_image, (seg.crop_region[0], seg.crop_region[1]), mask)
                 enhanced_list.append(enhanced_image)