Upload 2 files

app.py.text.111.txt

@@ -0,0 +1,51 @@
+from PIL import Image
+import cv2
+import gradio as gr
+import numpy as np
+import torch
+from accelerate import Accelerator
+from transformers import pipeline
+from diffusers.utils import load_image
+from diffusers import KandinskyV22PriorPipeline, KandinskyV22Pipeline
+
+accelerator = Accelerator(cpu=True)
+
+generator = torch.Generator(device="cpu").manual_seed(43)
+pope_prior = accelerator.prepare(KandinskyV22PriorPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-prior", torch_dtype=torch.float32))
+pope_prior = accelerator.prepare(pope_prior.to("cpu"))
+    
+pope = accelerator.prepare(KandinskyV22Pipeline.from_pretrained("kandinsky-community/kandinsky-2-2-decoder", torch_dtype=torch.float32))
+pope = accelerator.prepare(pope.to("cpu"))
+
+def plex(img, cook, one, two, three):
+    goof = load_image(img).resize((512, 512))
+    # We pass the prompt and negative prompt through the prior to generate image embeddings
+    prompt = cook
+    negative_prior_prompt = "lowres,text,bad quality,low quality,jpeg artifacts,ugly,bad hands,bad face,blurry,bad eyes,watermark,signature"
+    img_emb = pope_prior(prompt=prompt, image=goof, strength=0.85, num_prior_inference_steps=10, generator=generator)
+    negative_emb = pope_prior(prompt=negative_prior_prompt, image=goof, strength=1, num_neg_inference_steps=10, generator=generator)
+
+    # run text2img pipeline
+    imags = pope(
+    image_embeds=img_emb.image_embeds,
+    negative_image_embeds=negative_emb.image_embeds,
+    num_inference_steps=20,
+    generator=generator,
+    height=512,
+    width=512,
+    ).images[0]
+
+    ## return imags
+    images_texts = [cook, goof, imags]
+
+    # specify the weights for each condition in images_texts
+    weights = [one, two, three]
+
+    # We can leave the prompt empty
+    primpt = ""
+    prior_out = pope_prior.interpolate(images_texts, weights)
+    imas = pope(**prior_out, height=512, width=512).images[0]
+    return imas
+
+iface = gr.Interface(fn=plex,inputs=[gr.Image(label="drop", type="pil"), gr.Textbox(label="prompt"), gr.Slider(label="Text Guide",minimum=0.01,step=0.01,maximum=1,value=0.5), gr.Slider(label="Your Image Guide",minimum=0.01,step=0.01,maximum=1,value=0.5),gr.Slider(label="Generated Image Guide",minimum=0.01,step=0.01,maximum=1,value=0.3)], outputs=gr.Image(), title="Ksky22 Cntrl Gdd Interp", description="ksky22 Cntrl Gdd Interp")
+iface.launch()

requirements (33).txt

@@ -0,0 +1,9 @@
+gradio
+transformers
+torch
+numpy
+opencv-python
+diffusers
+controlnet_aux
+mediapipe
+accelerate