Merge pull request #9 from neph1/update-v1.8.0

add batch size

Author: neph1

sd_render/__init__.py

@@ -150,6 +150,11 @@ class StableDiffusionProperties(PropertyGroup):
         description="Height of the reference image (depth map)",
         default=512
     )
+    number_batches: IntProperty(
+        name="Batch size",
+        description="How many images to render in a batch",
+        default=1
+    )
     bake_texture: BoolProperty(
         name="Bake texture to object",
         description="Bake the generated image to the selected object",
@@ -306,6 +311,7 @@ def draw_generation_settings(layout, generate_image_properties):
     layout.prop(generate_image_properties, "cn_end")
     layout.prop(generate_image_properties, "ref_image_width")
     layout.prop(generate_image_properties, "ref_image_height")
+    layout.prop(generate_image_properties, "number_batches")
     layout.separator()
     layout.label(text="Backend settings")
     layout.prop(generate_image_properties, "sd_address")

sd_render/generate_texture.py

@@ -35,7 +35,10 @@ def render(props):
                                              cn_guidance=props.cn_guidance,
                                              depth_map=depth_map,
                                              scheduler=scheduler,
-                                             model=props.model)
+                                             model=props.model,
+                                             cn_start=props.cn_start,
+                                             cn_end=props.cn_end,
+                                             number_batches=props.number_batches)
     if props.return_image:
         generator.convert_image(image_data, props.output_image_name)
         try:

sd_render/image_gen/automatic1111.py

@@ -12,22 +12,22 @@ class Automatic1111(ImageGeneratorBase):
     def __init__(self, output_folder: str, address: str = '127.0.0.1', port: int = 7860) -> None:
         super().__init__("/sdapi/v1/txt2img", output_folder, address, port)
 
-    def generate_image(self, prompt: str, depth_map: str, negative_prompt: str = "text, watermark", seed: int = 0, sampler: str = "Euler a", steps: int = 30, cfg_scale: int = 7, width: int = 512, height: int = 512, cn_weight: float = 0.7, cn_guidance: float = 1, scheduler: str = None, model: str = '') -> str:
+    def generate_image(self, prompt: str, depth_map: str, negative_prompt: str = "text, watermark", seed: int = 0, sampler: str = "Euler a", steps: int = 30, cfg_scale: int = 7, width: int = 512, height: int = 512, cn_weight: float = 0.7, cn_guidance: float = 1, scheduler: str = None, model: str = '', cn_start: float = 0.0, cn_end: float = 1.0, number_batches: int = 1) -> str:
         if model:
             self.set_model(model)
-        image_data = self.send_request(prompt, depth_map, negative_prompt, seed, sampler, steps, cfg_scale, width, height, cn_weight, cn_guidance)
+        image_data = self.send_request(prompt, depth_map, negative_prompt, seed, sampler, steps, cfg_scale, width, height, cn_weight, cn_guidance, number_batches=number_batches)
         return image_data
 
 
-    def send_request(self, prompt, depth_map, negative_prompt: str, seed: int, sampler: str, steps: int, cfg_scale: int, width: int, height: int, cn_weight: float, cn_guidance: float) -> bytes:
+    def send_request(self, prompt, depth_map, negative_prompt: str, seed: int, sampler: str, steps: int, cfg_scale: int, width: int, height: int, cn_weight: float, cn_guidance: float, number_batches: int) -> bytes:
 
         data = {
             "prompt": prompt,
             "negative_prompt": negative_prompt,
             "alwayson_scripts": {},
             "seed": seed,
             "sampler_index": sampler,
-            "batch_size": 1,
+            "batch_size": number_batches,
             "n_iter": 1,
             "steps": steps,
             "cfg_scale": cfg_scale,

sd_render/image_gen/base_gen.py

@@ -13,6 +13,9 @@ def __init__(self, endpoint: str, output_folder:str, address: str = 'localhost',
         self.url = f"http://{self.address}:{self.port}"
         self.output_folder = output_folder
 
+    def generate_image(self, prompt: str, depth_map: str, negative_prompt: str = "text, watermark", seed: int = 0, sampler: str = "Euler a", steps: int = 30, cfg_scale: int = 7, width: int = 512, height: int = 512, cn_weight: float = 0.7, cn_guidance: float = 1, scheduler: str = None, model: str = '', cn_start: float = 0.0, cn_end: float = 1.0, number_batches: int = 1) -> str:
+        pass
+
     def convert_image(self, image_data: bytes, image_name):
         try:
             decoded_data = base64.b64decode(image_data)

sd_render/image_gen/comfy_ui.py

@@ -17,15 +17,15 @@ def __init__(self, output_folder: str, address: str = '127.0.0.1', port: int = 8
         super().__init__("/prompt", output_folder, address, port)
         self.workflow = workflow
 
-    def generate_image(self, prompt: str, depth_map: str, negative_prompt: str = "text, watermark", seed: int = -1, sampler: str = "euler", steps: int = 30, cfg_scale: float = 7, width: int = 512, height: int = 512, cn_weight: float = 0.7, cn_guidance: float = 1, scheduler: str = '', model: str = '', cn_start: float = 0.0, cn_end: float = 1.0) -> str:
+    def generate_image(self, prompt: str, depth_map: str, negative_prompt: str = "text, watermark", seed: int = -1, sampler: str = "euler", steps: int = 30, cfg_scale: float = 7, width: int = 512, height: int = 512, cn_weight: float = 0.7, cn_guidance: float = 1, scheduler: str = '', model: str = '', cn_start: float = 0.0, cn_end: float = 1.0, number_batches: int = 1) -> str:
         """Generate an image from text."""
-        image_data = self.send_request(prompt, depth_map, negative_prompt, seed, sampler, steps, cfg_scale, width, height, cn_weight, cn_guidance, scheduler, model, cn_start, cn_end)
+        image_data = self.send_request(prompt, depth_map, negative_prompt, seed, sampler, steps, cfg_scale, width, height, cn_weight, cn_guidance, scheduler, model, cn_start, cn_end, number_batches)
         if not image_data:
             return None
         return image_data[0]
 
 
-    def send_request(self, prompt, depth_map, negative_prompt: str, seed: int, sampler: str, steps: int, cfg_scale: int, width: int, height: int, cn_weight: float, cn_guidance: float, scheduler: str = '', model: str = '', cn_start: float = 1.0, cn_end: float = 1.0) -> bytes:
+    def send_request(self, prompt, depth_map, negative_prompt: str, seed: int, sampler: str, steps: int, cfg_scale: int, width: int, height: int, cn_weight: float, cn_guidance: float, scheduler: str = '', model: str = '', cn_start: float = 1.0, cn_end: float = 1.0, number_batches: int = 1) -> bytes:
 
         path = self._load_workflow(self.workflow)
         with open(path) as f:
@@ -44,7 +44,7 @@ def send_request(self, prompt, depth_map, negative_prompt: str, seed: int, sampl
         workflow = self._set_text_prompts(workflow, prompt, negative_prompt)
 
         workflow = self._set_sampler(workflow, sampler, cfg_scale, seed, steps, scheduler)
-        workflow = self._set_image_size(workflow, width, height)
+        workflow = self._set_image_size(workflow, width, height, number_batches)
 
         p = {"prompt": workflow}
         data = json.dumps(p)
@@ -126,9 +126,10 @@ def _set_sampler(self, data: dict, sampler: str, cfg: float, seed: int, steps: i
             data["3"]["inputs"]["scheduler"] = scheduler
         return data
 
-    def _set_image_size(self, data: dict, width: int = 512, height: int = 512) -> dict:
+    def _set_image_size(self, data: dict, width: int = 512, height: int = 512, batch_size: int = 1) -> dict:
         data["5"]["inputs"]["width"] = width
         data["5"]["inputs"]["height"] = height
+        data["5"]["inputs"]["batch_size"] = batch_size
         return data
 
     def _set_control_net(self, data:dict, depth_map: str, weight: float, guidance: float, start: float, end: float) -> dict: