Upload 5 files

Makefile

@@ -1,27 +1,27 @@
-install:
-	pip install --upgrade pip &&\
-		pip install -r requirements.txt
-
-test:
-	python -m pytest -vvv --cov=hello --cov=greeting \
-		--cov=smath --cov=web tests
-	python -m pytest --nbval notebook.ipynb	#tests our jupyter notebook
-	#python -m pytest -v tests/test_web.py #if you just want to test web
-
-debug:
-	python -m pytest -vv --pdb	#Debugger is invoked
-
-one-test:
-	python -m pytest -vv tests/test_greeting.py::test_my_name4
-
-debugthree:
-	#not working the way I expect
-	python -m pytest -vv --pdb --maxfail=4  # drop to PDB for first three failures
-
-format:
-	black *.py
-
-lint:
-	pylint --disable=R,C *.py
-
+install:
+	pip install --upgrade pip &&\
+		pip install -r requirements.txt
+
+test:
+	python -m pytest -vvv --cov=hello --cov=greeting \
+		--cov=smath --cov=web tests
+	python -m pytest --nbval notebook.ipynb	#tests our jupyter notebook
+	#python -m pytest -v tests/test_web.py #if you just want to test web
+
+debug:
+	python -m pytest -vv --pdb	#Debugger is invoked
+
+one-test:
+	python -m pytest -vv tests/test_greeting.py::test_my_name4
+
+debugthree:
+	#not working the way I expect
+	python -m pytest -vv --pdb --maxfail=4  # drop to PDB for first three failures
+
+format:
+	black *.py
+
+lint:
+	pylint --disable=R,C *.py
+
 all: install lint test format

app.py

@@ -1,7 +1,8 @@
-from PIL import Image
+from PIL import Image, ImageDraw, ImageFont, ImageEnhance
 import torch
 import torchvision
 import gradio
+import numpy as np
 
 Instructuction = "Select a Unique Portrait Image of yourself"
 title="I am something of a Painter, Anime-Edition (AnimeGAN-V2)"
@@ -27,12 +28,28 @@ face2paint = torch.hub.load(
     side_by_side=False
 )
 
+def enhance_logo_brightness(logo_image, factor):
+    enhancer = ImageEnhance.Brightness(logo_image)
+    return enhancer.enhance(factor)
+
+def add_logo(image):
+    logo_path = "./logo.jpg" # 로고 파일 경로
+    logo_size = (100, 30) # 로고 크기
+    logo = Image.open(logo_path).convert("RGBA")
+    logo = logo.resize(logo_size, resample=Image.BICUBIC)
+    logo = enhance_logo_brightness(logo, 1.5) # 로고 이미지의 밝기를 조절합니다.
+    return logo
+
 def inference(img):
-  return face2paint(model, img)
+    img_pil = Image.fromarray(img.astype('uint8'), 'RGB') # 이미지를 PIL 이미지 객체로 변환
+    output_image_pil = face2paint(model, img_pil.resize((512, 512))) # 이미지 변환
+    output_image_pil = output_image_pil.convert('RGB') # RGBA -> RGB 변환
+    logo = add_logo(output_image_pil) # 로고 이미지 가져오기
+    output_image_pil.paste(logo, (512 - logo.size[0], 512 - logo.size[1]), logo) # 로고 이미지를 생성된 이미지에 붙이기
+    output_image = np.array(output_image_pil) # PIL 이미지 객체를 numpy 배열로 변환
+    return output_image
 
 gradio.Interface(inference,
-                 inputs=gradio.Image(type='pil'),
-                 outputs=gradio.Image(type='pil'),
-                 Instructuction=Instructuction, title=title, description=description, article=article,
-                 examples=['Upload Xty.png',
-                           'Upload Tg.png']).launch()
+                 inputs=gradio.Image(type='numpy'),
+                 outputs=gradio.Image(type='numpy'),
+                 Instructuction=Instructuction, title=title, description=description, article=article).launch()

requirements.txt

@@ -1,3 +1,3 @@
-gradio
-torch
-torchvision
+gradio
+torch
+torchvision