Remove 8x

app.py

@@ -135,7 +135,7 @@ with gr.Blocks(
                             label="Images",
                         )
                         scale = gr.Dropdown(
-                            choices=[("1x", 1), ("2x", 2), ("4x", 4), ("8x", 8)],
+                            choices=[("1x", 1), ("2x", 2), ("4x", 4)],
                             filterable=False,
                             label="Scale",
                             min_width=200,

cli.py

@@ -24,7 +24,7 @@ def main():
     parser.add_argument("-h", "--height", type=int, metavar="INT", default=cfg.HEIGHT)
     parser.add_argument("-m", "--model", type=str, metavar="STR", default=cfg.MODEL)
     parser.add_argument("-d", "--deepcache", type=int, metavar="INT", default=cfg.DEEPCACHE_INTERVAL)
-    parser.add_argument("--scale", type=int, metavar="INT", default=1)
+    parser.add_argument("--scale", type=int, metavar="INT", choices=[1, 2, 4], default=1)
     parser.add_argument("--style", type=str, metavar="STR", default=cfg.STYLE)
     parser.add_argument("--scheduler", type=str, metavar="STR", default=cfg.SCHEDULER)
     parser.add_argument("--guidance", type=float, metavar="FLOAT", default=cfg.GUIDANCE_SCALE)

lib/upscaler.py

@@ -267,7 +267,7 @@ class RealESRGAN:
         )
 
     def load_weights(self):
-        assert self.scale in [2, 4, 8], "You can download models only with scales: 2, 4, 8"
+        assert self.scale in [2, 4], "You can download models only with scales: 2, 4"
         config = HF_MODELS[self.scale]
         cache_path = hf_hub_download(config["repo_id"], filename=config["filename"])
         loadnet = torch.load(cache_path)