test

app.py

@@ -23,10 +23,24 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 # helper.enable()
 # pipe.compile()
 
-def resize(value,img):
-    img = Image.open(img)
-    img = img.resize((value,value))
-    return img
+def resize(target_size,source):
+    original_width,original_height =source.size
+    aspect_ratio = original_height / original_width
+   
+    # 计算新的高度以保持宽高比，假设我们先确定宽度为512像素
+    new_width = target_size
+    new_height = int(new_width*aspect_ratio)
+   
+    # 如果新高度超过目标大小，则重新计算宽度以保持目标高度
+    if new_height > target_size:
+        new_height = target_size
+        new_width = int(new_height / aspect_ratio)
+    print("宽高",original_height,original_width,aspect_ratio,new_height)
+    # 等比例缩放图片
+    # resized_image = Image.fromarray(image_array).resize((new_width, new_height), resample=Image.LANCZOS)
+    resized_image =source.resize((new_width, new_height))
+    return resized_image
+   
 
 def infer(model_id,source_img, prompt, steps, seed, Strength):
     pipe = OVStableDiffusionImg2ImgPipeline.from_pretrained(model_id, torch_dtype=torch.float16, export=True) if torch.cuda.is_available() else AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo")
@@ -48,7 +62,7 @@ def infer(model_id,source_img, prompt, steps, seed, Strength):
     return image
 
 gr.Interface(fn=infer, inputs=[
-    gr.Text(value="Lykon/dreamshaper-xl-v2-turbo", label="Checkpoint"),
+    gr.Text(value="IDKiro/sdxs-512-dreamshaper", label="Checkpoint"),
     gr.Image(sources=["upload", "webcam", "clipboard"], type="filepath", label="Raw Image."), 
     gr.Textbox(label = 'Prompt Input Text. 77 Token (Keyword or Symbol) Maximum'),
     gr.Slider(1, 5, value = 2, step = 1, label = 'Number of Iterations'),