add parameters

handler.py

@@ -146,7 +146,19 @@ class EndpointHandler():
         self.app = FaceAnalysis(name="buffalo_l", root="./", providers=["CPUExecutionProvider"])
         self.app.prepare(ctx_id=0, det_size=(640, 640))
         
-    def __call__(self, param):
+    def __call__(self, data):
+        
+        
+        default_prompt = "watercolor painting, {prompt}. vibrant, beautiful, painterly, detailed, textural, artistic"
+        default_negative_prompt = "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, anime, photorealistic, 35mm film, deformed, glitch, low contrast, noisy"
+
+        # hyperparamters
+        prompt_input = data.pop("inputs", "a man")
+        prompt=default_prompt.replace("{prompt}", prompt_input)
+        num_inference_steps = data.pop("num_inference_steps", 5)
+        guidance_scale = data.pop("guidance_scale", 1.5)
+        negative_prompt = data.pop("negative_prompt", default_negative_prompt)
+        
         self.pipe.scheduler = diffusers.LCMScheduler.from_config(self.pipe.scheduler.config)
         self.pipe.enable_lora()
         
@@ -155,7 +167,7 @@ class EndpointHandler():
         pose_strength = 0.4
         canny_strength = 0.3
         # depth_strength = 0.5
-        controlnet_selection = ["pose", "canny"]
+        controlnet_selection = ["pose"]
         # controlnet_selection = ["pose", "canny", "depth"]
         
         face_image_path = "https://i.ibb.co/SKg69dD/kaifu-resize.png"
@@ -205,8 +217,6 @@ class EndpointHandler():
         #     )
         #  check the prompt
         # if prompt is None:
-        prompt = "watercolor painting, a man. vibrant, beautiful, painterly, detailed, textural, artistic"
-        negative_prompt = "(lowres, low quality, worst quality:1.2), (text:1.2), watermark, anime, photorealistic, 35mm film, deformed, glitch, low contrast, noisy"
         
         # apply the style template
         # prompt, negative_prompt = apply_style(style_name, prompt, negative_prompt)
@@ -297,8 +307,8 @@ class EndpointHandler():
             image=control_images,
             control_mask=control_mask,
             controlnet_conditioning_scale=control_scales,
-            num_inference_steps=5,
-            guidance_scale=1.5,
+            num_inference_steps=num_inference_steps,
+            guidance_scale=guidance_scale,
             height=height,
             width=width,
             generator=generator,