change adapter

app_haircolor.py

@@ -38,20 +38,15 @@ pidinet_detector = pidinet_detector.to(DEVICE)
 
 canndy_detector = CannyDetector()
 
-midas_detector = MidasDetector.from_pretrained(
-    "valhalla/t2iadapter-aux-models", filename="dpt_large_384.pt", model_type="dpt_large"
-)
-midas_detector = midas_detector.to(DEVICE)
-
 adapters = MultiAdapter(
     [
         T2IAdapter.from_pretrained(
-            "TencentARC/t2i-adapter-lineart-sdxl-1.0",
+            "TencentARC/t2iadapter_sketch_sd15v2",
             torch_dtype=torch.float16,
             varient="fp16",
         ),
         T2IAdapter.from_pretrained(
-            "TencentARC/t2i-adapter-canny-sdxl-1.0",
+            "TencentARC/t2iadapter_canny_sd15v2",
             torch_dtype=torch.float16,
             varient="fp16",
         )
@@ -85,12 +80,13 @@ def image_to_image(
     run_task_time = 0
     time_cost_str = ''
     run_task_time, time_cost_str = get_time_cost(run_task_time, time_cost_str)
-    lineart_image = lineart_detector(input_image, int(generate_size*0.375), generate_size)
-    run_task_time, time_cost_str = get_time_cost(run_task_time, time_cost_str)
+    # lineart_image = lineart_detector(input_image, int(generate_size*0.375), generate_size)
+    # run_task_time, time_cost_str = get_time_cost(run_task_time, time_cost_str)
     canny_image = canndy_detector(input_image, int(generate_size*0.375), generate_size)
     run_task_time, time_cost_str = get_time_cost(run_task_time, time_cost_str)
+    sketch_image = pidinet_detector(input_image, int(generate_size*0.5), generate_size)
 
-    cond_image = [lineart_image, canny_image]
+    cond_image = [sketch_image, canny_image]
     cond_scale = [lineart_scale, canny_scale]
 
     generator = torch.Generator(device=DEVICE).manual_seed(seed)