Update app.py

app.py

@@ -7,6 +7,11 @@ import pandas as pd
 from PIL import Image
 from huggingface_hub import hf_hub_download
 from onnxruntime import InferenceSession
+from fastapi import FastAPI, File, UploadFile,Body,Query,Response
+import uvicorn
+app = FastAPI()
+
+
 
 # noinspection PyUnresolvedReferences
 def make_square(img, target_size):
@@ -175,32 +180,15 @@ def image_to_wd14_tags(image: Image.Image, model_name: str, threshold: float,
     return ratings, output_text, filtered_tags
 
 
-if __name__ == '__main__':
-    with gr.Blocks(analytics_enabled=False, theme="NoCrypt/miku") as demo:
-        with gr.Row():
-            with gr.Column():
-                gr_input_image = gr.Image(type='pil', label='Chen Chen', sources=['upload', 'clipboard'])
-                with gr.Row():
-                    gr_model = gr.Radio(list(WAIFU_MODELS.keys()), value='chen-moat2', label='Chen')
-                    gr_threshold = gr.Slider(0.0, 1.0, 0.5, label='Chen Chen Chen Chen Chen')
-                with gr.Row():
-                    gr_space = gr.Checkbox(value=True, label='Use DashSpace')
-                    gr_escape = gr.Checkbox(value=True, label='Chen Text Escape')
-
-                gr_btn_submit = gr.Button(value='橙', variant='primary')
-
-            with gr.Column():
-                gr_ratings = gr.Label(label='橙 橙')
-                with gr.Tabs():
-                    with gr.Tab("Chens"):
-                        gr_tags = gr.Label(label='Chens')
-                    with gr.Tab("Chen Text"):
-                        gr_output_text = gr.TextArea(label='Chen Text')
-
-        gr_btn_submit.click(
-            image_to_wd14_tags,
-            inputs=[gr_input_image, 'chen-moat2', 0.5, True, True],
-            outputs=[gr_ratings, gr_output_text, gr_tags],
-            api_name="classify"
-        )
-    demo.queue(os.cpu_count()).launch()
+#获取图片调用image_to_wd14_tags函数获取返回
+@app.post("/getOriginalMangaList") #增加指定保存路径功能,默认是/manga路径
+def getOriginalMangaList(image: UploadFile = File(...))->"ratings, output_text, filtered_tags":
+    
+    img = image.file.read()
+    image_data = Image.open(io.BytesIO(img)).convert("L").convert("RGB")
+    
+    return image_to_wd14_tags(image_data,'chen-moat2',0.5,True,True)
+
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)