Upload sd_controller.py

sd/sd_controller.py

@@ -29,46 +29,46 @@ class Controller():
                                   scheduler=self.scheduler)
 
 
-        @spaces.GPU
-        def get_first_result(self, img, prompt, negative_prompt, 
-                             controlnet_scale=0.5, strength=1.0,n_steps=30,eta=1.0):
-
-            substrate, resized_image = sketch_process(input_image)
-            prompt=prompt_preprocess(prompt)
-
-            result=self.first_pipe(image=substrate,
-                                    control_image=resized_image,
-                                    strength=strength,
-                                    prompt=prompt,
-                                    negative_prompt = negative_prompt,
-                                    controlnet_conditioning_scale=float(controlnet_scale),
-                                    generator=torch.manual_seed(0),
-                                    num_inference_steps=n_steps,
-                                    eta=eta)
-
-            return result.images[0]
-
-
-        @spaces.GPU
-        def get_second_result(self, img, prompt, negative_prompt,
-                              g_scale=7.5, n_steps=25, 
-                              adapter_scale=0.9, adapter_factor=1.0):
-
-            preprocessed_img=self.detector(img, 
-                                             detect_resolution=1024, 
-                                             image_resolution=1024,
-                                             apply_filter=True).convert("L")
-
-            result=self.second_pipe(prompt=prompt,
-                                    negative_prompt=negative_prompt,
-                                    image=image_preprocessed,
-                                    guidance_scale=g_scale,
-                                    num_inference_steps=n_steps,
-                                    adapter_conditioning_scale=adapter_scale,
-                                    adapter_conditioning_factor=adapter_factor,
-                                    generator = torch.manual_seed(42))
-
-            return result.images[0]
+    @spaces.GPU
+    def get_first_result(self, img, prompt, negative_prompt, 
+                         controlnet_scale=0.5, strength=1.0,n_steps=30,eta=1.0):
+
+        substrate, resized_image = sketch_process(input_image)
+        prompt=prompt_preprocess(prompt)
+
+        result=self.first_pipe(image=substrate,
+                                control_image=resized_image,
+                                strength=strength,
+                                prompt=prompt,
+                                negative_prompt = negative_prompt,
+                                controlnet_conditioning_scale=float(controlnet_scale),
+                                generator=torch.manual_seed(0),
+                                num_inference_steps=n_steps,
+                                eta=eta)
+
+        return result.images[0]
+
+
+    @spaces.GPU
+    def get_second_result(self, img, prompt, negative_prompt,
+                          g_scale=7.5, n_steps=25, 
+                          adapter_scale=0.9, adapter_factor=1.0):
+
+        preprocessed_img=self.detector(img, 
+                                         detect_resolution=1024, 
+                                         image_resolution=1024,
+                                         apply_filter=True).convert("L")
+
+        result=self.second_pipe(prompt=prompt,
+                                negative_prompt=negative_prompt,
+                                image=preprocessed_img,
+                                guidance_scale=g_scale,
+                                num_inference_steps=n_steps,
+                                adapter_conditioning_scale=adapter_scale,
+                                adapter_conditioning_factor=adapter_factor,
+                                generator = torch.manual_seed(42))
+
+        return result.images[0]