Clean up

app.py

@@ -1,11 +1,8 @@
 import math
-import os
 import random
 
 import cv2
-import diffusers
 import gradio as gr
-import insightface
 import numpy as np
 import PIL
 import spaces
@@ -40,8 +37,8 @@ app = FaceAnalysis(name="antelopev2", root="./", providers=["CPUExecutionProvide
 app.prepare(ctx_id=0, det_size=(640, 640))
 
 # Path to InstantID models
-face_adapter = f"./checkpoints/ip-adapter.bin"
-controlnet_path = f"./checkpoints/ControlNetModel"
+face_adapter = "./checkpoints/ip-adapter.bin"
+controlnet_path = "./checkpoints/ControlNetModel"
 
 # Load pipeline
 controlnet = ControlNetModel.from_pretrained(controlnet_path, torch_dtype=torch.float16)
@@ -221,7 +218,7 @@ def generate_image(
     progress=gr.Progress(track_tqdm=True),
 ):
     if face_image is None:
-        raise gr.Error(f"Cannot find any input face image! Please upload the face image")
+        raise gr.Error("Cannot find any input face image! Please upload the face image")
 
     if prompt is None:
         prompt = "a person"
@@ -238,7 +235,7 @@ def generate_image(
     face_info = app.get(face_image_cv2)
 
     if len(face_info) == 0:
-        raise gr.Error(f"Cannot find any face in the image! Please upload another person image")
+        raise gr.Error("Cannot find any face in the image! Please upload another person image")
 
     face_info = sorted(
         face_info,
@@ -257,7 +254,7 @@ def generate_image(
         face_info = app.get(pose_image_cv2)
 
         if len(face_info) == 0:
-            raise gr.Error(f"Cannot find any face in the reference image! Please upload another person image")
+            raise gr.Error("Cannot find any face in the reference image! Please upload another person image")
 
         face_info = face_info[-1]
         face_kps = draw_kps(pose_image, face_info["kps"])
@@ -484,6 +481,5 @@ with gr.Blocks(css=css) as demo:
 
     gr.Markdown(article)
 
-
 demo.queue(api_open=False)
 demo.launch()