i

launch.py

@@ -18,7 +18,7 @@ def prepare_environment():
 
     xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.20')
 
-    comfy_repo = os.environ.get('COMFY_REPO', "https://github.com/comfyanonymous/ComfyUI.git")
+    comfy_repo = os.environ.get('COMFY_REPO', "https://github.com/lllyasviel/ComfyUI-Embedded.git")
     comfy_commit_hash = os.environ.get('COMFY_COMMIT_HASH', "5ac96897e9782805cd5e8fe85bd98ad03eae2b6f")
 
     commit = commit_hash()

modules/sd.py

@@ -0,0 +1,50 @@
+import os
+import random
+import torch
+import numpy as np
+
+from comfy.sd import load_checkpoint_guess_config
+from nodes import VAEDecode, KSamplerAdvanced, EmptyLatentImage, CLIPTextEncode
+from modules.path import modelfile_path
+
+
+xl_base_filename = os.path.join(modelfile_path, 'sd_xl_base_1.0.safetensors')
+xl_refiner_filename = os.path.join(modelfile_path, 'sd_xl_refiner_1.0.safetensors')
+
+xl_base, xl_base_clip, xl_base_vae, xl_base_clipvision = load_checkpoint_guess_config(xl_base_filename)
+del xl_base_clipvision
+
+opCLIPTextEncode = CLIPTextEncode()
+opEmptyLatentImage = EmptyLatentImage()
+opKSamplerAdvanced = KSamplerAdvanced()
+opVAEDecode = VAEDecode()
+
+with torch.no_grad():
+    positive_conditions = opCLIPTextEncode.encode(clip=xl_base_clip, text='a handsome man in forest')[0]
+    negative_conditions = opCLIPTextEncode.encode(clip=xl_base_clip, text='bad, ugly')[0]
+
+    initial_latent_image = opEmptyLatentImage.generate(width=1024, height=1024, batch_size=1)[0]
+
+    samples = opKSamplerAdvanced.sample(
+        add_noise="enable",
+        noise_seed=random.randint(1, 2 ** 64),
+        steps=25,
+        cfg=9,
+        sampler_name="euler",
+        scheduler="normal",
+        start_at_step=0,
+        end_at_step=25,
+        return_with_leftover_noise="enable",
+        model=xl_base,
+        positive=positive_conditions,
+        negative=negative_conditions,
+        latent_image=initial_latent_image,
+    )[0]
+
+    vae_decoded = opVAEDecode.decode(samples=samples, vae=xl_base_vae)[0]
+
+    for image in vae_decoded:
+        i = 255. * image.cpu().numpy()
+        img = np.clip(i, 0, 255).astype(np.uint8)
+        import cv2
+        cv2.imwrite('a.png', img[:, :, ::-1])