Spaces:
Running
Running
model update
Browse files- backend/safety_check.py +2 -2
- frontend/webui/hf_demo.py +12 -3
backend/safety_check.py
CHANGED
|
@@ -2,8 +2,8 @@ from transformers import CLIPProcessor, CLIPModel
|
|
| 2 |
from PIL import Image
|
| 3 |
|
| 4 |
|
| 5 |
-
model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32")
|
| 6 |
-
processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
|
| 7 |
|
| 8 |
|
| 9 |
def is_safe_image(
|
|
|
|
| 2 |
from PIL import Image
|
| 3 |
|
| 4 |
|
| 5 |
+
# model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32")
|
| 6 |
+
# processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
|
| 7 |
|
| 8 |
|
| 9 |
def is_safe_image(
|
frontend/webui/hf_demo.py
CHANGED
|
@@ -9,15 +9,19 @@ import base64
|
|
| 9 |
from backend.device import get_device_name
|
| 10 |
from constants import APP_VERSION
|
| 11 |
from backend.device import is_openvino_device
|
| 12 |
-
import
|
| 13 |
from backend.models.lcmdiffusion_setting import DiffusionTask
|
|
|
|
| 14 |
from pprint import pprint
|
|
|
|
| 15 |
|
| 16 |
lcm_text_to_image = LCMTextToImage()
|
| 17 |
lcm_lora = LCMLora(
|
| 18 |
base_model_id="Lykon/dreamshaper-7",
|
| 19 |
lcm_lora_id="latent-consistency/lcm-lora-sdv1-5",
|
| 20 |
)
|
|
|
|
|
|
|
| 21 |
|
| 22 |
|
| 23 |
# https://github.com/gradio-app/gradio/issues/2635#issuecomment-1423531319
|
|
@@ -56,7 +60,7 @@ def predict(
|
|
| 56 |
# lcm_diffusion_setting.image_height = 320 if is_openvino_device() else 512
|
| 57 |
lcm_diffusion_setting.image_width = 512
|
| 58 |
lcm_diffusion_setting.image_height = 512
|
| 59 |
-
lcm_diffusion_setting.use_openvino =
|
| 60 |
lcm_diffusion_setting.use_tiny_auto_encoder = False
|
| 61 |
pprint(lcm_diffusion_setting.model_dump())
|
| 62 |
lcm_text_to_image.init(lcm_diffusion_setting=lcm_diffusion_setting)
|
|
@@ -64,7 +68,12 @@ def predict(
|
|
| 64 |
images = lcm_text_to_image.generate(lcm_diffusion_setting)
|
| 65 |
latency = perf_counter() - start
|
| 66 |
print(f"Latency: {latency:.2f} seconds")
|
| 67 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 68 |
|
| 69 |
|
| 70 |
css = """
|
|
|
|
| 9 |
from backend.device import get_device_name
|
| 10 |
from constants import APP_VERSION
|
| 11 |
from backend.device import is_openvino_device
|
| 12 |
+
from PIL import Image
|
| 13 |
from backend.models.lcmdiffusion_setting import DiffusionTask
|
| 14 |
+
from backend.safety_check import is_safe_image
|
| 15 |
from pprint import pprint
|
| 16 |
+
from transformers import CLIPProcessor, CLIPModel
|
| 17 |
|
| 18 |
lcm_text_to_image = LCMTextToImage()
|
| 19 |
lcm_lora = LCMLora(
|
| 20 |
base_model_id="Lykon/dreamshaper-7",
|
| 21 |
lcm_lora_id="latent-consistency/lcm-lora-sdv1-5",
|
| 22 |
)
|
| 23 |
+
model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32")
|
| 24 |
+
processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
|
| 25 |
|
| 26 |
|
| 27 |
# https://github.com/gradio-app/gradio/issues/2635#issuecomment-1423531319
|
|
|
|
| 60 |
# lcm_diffusion_setting.image_height = 320 if is_openvino_device() else 512
|
| 61 |
lcm_diffusion_setting.image_width = 512
|
| 62 |
lcm_diffusion_setting.image_height = 512
|
| 63 |
+
lcm_diffusion_setting.use_openvino = True
|
| 64 |
lcm_diffusion_setting.use_tiny_auto_encoder = False
|
| 65 |
pprint(lcm_diffusion_setting.model_dump())
|
| 66 |
lcm_text_to_image.init(lcm_diffusion_setting=lcm_diffusion_setting)
|
|
|
|
| 68 |
images = lcm_text_to_image.generate(lcm_diffusion_setting)
|
| 69 |
latency = perf_counter() - start
|
| 70 |
print(f"Latency: {latency:.2f} seconds")
|
| 71 |
+
result = images[0]
|
| 72 |
+
if is_safe_image(model, processor, result):
|
| 73 |
+
return result # .resize([512, 512], PIL.Image.ANTIALIAS)
|
| 74 |
+
else:
|
| 75 |
+
print("Unsafe image detected")
|
| 76 |
+
return Image.new("RGB", (512, 512), (0, 0, 0))
|
| 77 |
|
| 78 |
|
| 79 |
css = """
|