F

app.py

@@ -1,13 +1,13 @@
 import os
 import gradio as gr
 import util
-import run_cmd as run
+from run_cmd import run_cmd
 from random import randint
 from PIL import Image
 
 is_colab = util.is_google_colab()
 
-run("pip install pngquant")
+run_cmd("pip install pngquant")
 
 def inference(img, size, type):
     _id = randint(1, 10000)
@@ -15,16 +15,16 @@ def inference(img, size, type):
     OUTPUT_DIR = "/tmp/output_image" + str(_id) + "/"
     img_in_path = os.path.join(INPUT_DIR, "1.jpg")
     img_out_path = os.path.join(OUTPUT_DIR, "1_out.png")
-    run(f"rm -rf {INPUT_DIR}")
-    run(f"rm -rf {OUTPUT_DIR}")
-    run(f"mkdir {INPUT_DIR}")
-    run(f"mkdir {OUTPUT_DIR}")
+    run_cmd(f"rm -rf {INPUT_DIR}")
+    run_cmd(f"rm -rf {OUTPUT_DIR}")
+    run_cmd(f"mkdir {INPUT_DIR}")
+    run_cmd(f"mkdir {OUTPUT_DIR}")
     img.save(img_in_path, "PNG")
 
     if type == "Manga":
-        run(f"python inference_manga_v2.py {img_in_path} {img_out_path}")
+        run_cmd(f"python inference_manga_v2.py {img_in_path} {img_out_path}")
     else:
-        run(f"python inference.py {img_in_path} {img_out_path} {type}")
+        run_cmd(f"python inference.py {img_in_path} {img_out_path} {type}")
 
     img_out = Image.open(img_out_path)
 
@@ -35,8 +35,8 @@ def inference(img, size, type):
     #img_out = Image.open(img_out_path)
 
     # Remove input and output image
-    run(f"rm -f {img_in_path}")
-    run(f"rm -f {img_out_path}")
+    run_cmd(f"rm -f {img_in_path}")
+    run_cmd(f"rm -f {img_out_path}")
 
     return [img_out]