documentation

README.md

@@ -1 +1,33 @@
-# Control net test
+---
+license: openrail
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- controlnet
+- endpoints-template
+inference: true
+---
+
+# Control Net SD with safe chekers
+
+### expected Request payload
+
+```json
+{
+    "prompt": "A prompt used for image generation",
+    "negative_prompt": "low res, bad anatomy, worst quality, low quality",
+    "image_depth_map" : "iVBORw0KGgoAAAANSUhEUgAAAgAAAAIACAIAAAB7GkOtAAAABGdBTUEAALGPC",
+    "steps": 25,
+    "scale": 7,
+    "height": 512,
+    "width": 512,
+    "controlnet_conditioning_scale": 1,
+    "sd_model": "dreamshaper"
+}
+```
+
+SD_MODEL no tested 
+
+default => Lykon/dreamshaper-8
+
+dreamshaper || juggernaut || realistic-vision || rev-animated

handler.py

@@ -43,23 +43,21 @@ class EndpointHandler():
 
     def __call__(self, data: Any) -> List[List[Dict[str, float]]]:
         """
-        :param data: A dictionary contains `inputs` and optional `image` field.
+        :param data: A dictionary contains `prompt` and optional `image_depth_map` field.
         :return: A dictionary with `image` field contains image in base64.
         """
         
 
         # hyperparamters
         sd_model = data.pop("sd_model", None)
-        prompt = data.pop("inputs", None)
+        prompt = data.pop("prompt", None)
         negative_prompt = data.pop("negative_prompt", None)
         image_depth_map = data.pop("image_depth_map", None)
-        num_inference_steps = data.pop("num_inference_steps", 25)
-        guidance_scale = data.pop("guidance_scale", 7)
-        
-        
+        steps = data.pop("steps", 25)
+        scale = data.pop("scale", 7)
         height = data.pop("height", None)
         width = data.pop("width", None)
-        controlnet_conditioning_scale = data.pop("controlnet_conditioning_scale", 1.0)
+        controlnet_conditioning_scale = data.pop("controlnet_conditioning_scale", 1)
 
         self.stable_diffusion_id = SD_ID_MAPPING.get(sd_model, "Lykon/dreamshaper-8")
 
@@ -86,8 +84,8 @@ class EndpointHandler():
             prompt=prompt, 
             negative_prompt=negative_prompt,
             image=image,
-            num_inference_steps=num_inference_steps, 
-            guidance_scale=guidance_scale,
+            num_inference_steps=steps, 
+            guidance_scale=scale,
             num_images_per_prompt=1,
             height=height,
             width=width,