@ -78,7 +78,7 @@ class Pipeline:
use_tiny_vae=True,
device=device,
dtype=torch_dtype,
t_index_list=[8, 32],
t_index_list=[1,16],
# t_index_list=[1],
frame_buffer_size=1,
width=params.width,
@ -101,8 +101,8 @@ class Pipeline:
self.stream.prepare(
prompt=default_prompt,
negative_prompt=default_negative_prompt,
num_inference_steps=50,
guidance_scale=0.2,
num_inference_steps=30,
guidance_scale=0.9,
)
def predict(self, image: Image.Image, params: "Pipeline.InputParams") -> Image.Image:
@ -82,9 +82,10 @@ def main():
continue
image_rgb_array = image_bgra[:, :, [2,1,0]]
image_rgb_array = (image_rgb_array+ 1.0 )/2.0
#image_rgb_array = (image_rgb_array+ 1.0 )/2.0
input_image = Image.fromarray(image_rgb_array, 'RGB')
# input_image.save("debug_input.png")
#print(f"Input size:{input_image.size}")
if not prompt_queue.empty():
new_prompt = prompt_queue.get(block=False)