全新基于fastapi设计japi的架构

requirements.txt

@@ -0,0 +1,8 @@
+requests>=2.31.0
+Pillow>=10.0.0
+torch>=2.0.0
+transformers>=4.30.0
+fastapi>=0.104.0
+uvicorn>=0.23.2
+python-multipart>=0.0.6
+pydantic>=2.4.2

task/requirements.txt

@@ -1,4 +0,0 @@
-requests>=2.31.0
-Pillow>=10.0.0
-torch>=2.0.0
-transformers>=4.30.0

task/rmbg.py

@@ -1,106 +0,0 @@
-import os
-import gradio as gr
-from gradio_imageslider import ImageSlider
-from loadimg import load_img
-import spaces
-from transformers import AutoModelForImageSegmentation
-import torch
-from torchvision import transforms
-
-torch.set_float32_matmul_precision(["high", "highest"][0])
-
-birefnet = AutoModelForImageSegmentation.from_pretrained(
-    "briaai/RMBG-2.0", trust_remote_code=True
-)
-birefnet.to("cuda")
-transform_image = transforms.Compose(
-    [
-        transforms.Resize((1024, 1024)),
-        transforms.ToTensor(),
-        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]),
-    ]
-)
-
-output_folder = 'output_images'
-if not os.path.exists(output_folder):
-    os.makedirs(output_folder)
-
-def fn(image):
-    im = load_img(image, output_type="pil")
-    im = im.convert("RGB")
-    origin = im.copy()
-    image = process(im)    
-    image_path = os.path.join(output_folder, "no_bg_image.png")
-    image.save(image_path)
-    return (image, origin), image_path
-
-@spaces.GPU
-def process(image):
-    image_size = image.size
-    input_images = transform_image(image).unsqueeze(0).to("cuda")
-    # Prediction
-    with torch.no_grad():
-        preds = birefnet(input_images)[-1].sigmoid().cpu()
-    pred = preds[0].squeeze()
-    pred_pil = transforms.ToPILImage()(pred)
-    mask = pred_pil.resize(image_size)
-    image.putalpha(mask)
-    return image
-  
-def process_file(f):
-    name_path = f.rsplit(".",1)[0]+".png"
-    im = load_img(f, output_type="pil")
-    im = im.convert("RGB")
-    transparent = process(im)
-    transparent.save(name_path)
-    return name_path
-
-slider1 = ImageSlider(label="RMBG-2.0", type="pil")
-slider2 = ImageSlider(label="RMBG-2.0", type="pil")
-image = gr.Image(label="Upload an image")
-image2 = gr.Image(label="Upload an image",type="filepath")
-text = gr.Textbox(label="Paste an image URL")
-png_file = gr.File(label="output png file")
-
-
-chameleon = load_img("giraffe.jpg", output_type="pil")
-
-url = "http://farm9.staticflickr.com/8488/8228323072_76eeddfea3_z.jpg"
-
-tab1 = gr.Interface(
-    fn, inputs=image, outputs=[slider1, gr.File(label="output png file")], examples=[chameleon], api_name="image"
-)
-
-tab2 = gr.Interface(fn, inputs=text, outputs=[slider2, gr.File(label="output png file")], examples=[url], api_name="text")
-tab3 = gr.Interface(process_file, inputs=image2, outputs=png_file, examples=["giraffe.jpg"], api_name="png")
-
-
-demo = gr.TabbedInterface(
-    [tab1, tab2], ["input image", "input url"], title = (
-    "RMBG-2.0 for background removal <br>"
-    "<span style='font-size:16px; font-weight:300;'>"
-    "Background removal model developed by "
-    "<a href='https://bria.ai' target='_blank'>BRIA.AI</a>, trained on a carefully selected dataset,<br> "
-    "and is available as an open-source model for non-commercial use.</span><br>"
-    "<span style='font-size:16px; font-weight:500;'> For testing upload your image and wait.<br>"
-    "<a href='https://go.bria.ai/3ZCBTLH' target='_blank'>Commercial use license</a> | "
-    "<a href='https://huggingface.co/briaai/RMBG-2.0' target='_blank'>Model card</a> | "
-    "<a href='https://blog.bria.ai/brias-new-state-of-the-art-remove-background-2.0-outperforms-the-competition' target='_blank'>Blog</a>"
-    "</span><br>"
-    "<span style='font-size:16px; font-weight:300;'>"
-    "API Endpoint available on: "
-    "<a href='https://platform.bria.ai/console/api/image-editing' target='_blank'>Bria.ai</a>, "
-    "<a href='https://fal.ai/models/fal-ai/bria/background/remove' target='_blank'>fal.ai</a><br>"
-    "ComfyUI node is available here: "
-    "<a href='https://github.com/Bria-AI/ComfyUI-BRIA-API' target='_blank'>ComfyUI Node</a><br>"
-    "Purchase commercial weigths for commercial use: "
-    "<a href='https://go.bria.ai/3D5EGp0' target='_blank'>here</a>"
-    "</span>"
-)
-
-
-
-)
-
-if __name__ == "__main__":
-    demo.launch(show_error=True)