Adding img2img step

app.py

@@ -4,6 +4,13 @@ import random
 from PIL import Image
 import cv2
 
+from diffusers import StableDiffusionImg2ImgPipeline
+
+
+model_id_or_path = "runwayml/stable-diffusion-v1-5"
+pipe = StableDiffusionImg2ImgPipeline.from_pretrained(model_id_or_path, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
+
 import gradio as gr
 from glob import glob
 from omegaconf import OmegaConf
@@ -216,11 +223,18 @@ class AnimateController:
         image.resize((512, 512))
 
          # Save the resized image to the specified output path
-        image.save("resized.jpg")
+        #image.save("resized.jpg")
+
+        
+
+        # Convert the image to SD by Img2Img pipeline
+
+        sd_images = pipe(prompt=prompt_textbox, image=init_image, strength=0.75, guidance_scale=7.5).images
+        sd_images[0].save("sd_converted.png")
         
         sample = pipeline(
             prompt_textbox,
-            init_image          = "resized.jpg",
+            init_image          = "sd_converted.jpg",
             negative_prompt     = negative_prompt_textbox,
             num_inference_steps = 25,
             guidance_scale      = 8.,