Update app.py

app.py

@@ -1,35 +1,21 @@
-
-from tensorflow.keras.models import load_model
-import tensorflow as tf
-import os
+import random
+import re
 import torch
-from diffusers import StableDiffusionPipeline
+import requests
+from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler
 from torch import autocast
+import gradio as gr
 
+def txt2img(prompt):
 
-model_path = "Fung804/makoto-shinkai-v2"
-pipe = StableDiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float16)
-pipe.to("cuda")
-pipe.vae.enable_tiling()
-
-prompt = "A train track with a sky background , realistic, highly detailed, high quality" #@param {type:"string"}
-negative_prompt = "((low quality)),((poor quality)),((clone)),retro style, bad anatomy,((lowres)), blurry, (worst quality), ((low quality)), normal quality,bad anatomy, disfigured, deformed, mutation, mutilated, ugly, totem pole,(poorly drawn face), cloned face, several faces, long neck, mutated hands, bad hands, poorly drawn hands,extra limbs, malformed limbs, missing arms, missing fingers, extra fingers, fused fingers, too many fingers,missing legs, extra legs, malformed legs, extra digit, fewer digits, glitchy, cropped, jpeg artifacts, signature, watermark, username, text, errorretro style ,bad anatomy,((lowres)), blurry, (worst quality), normal quality,bad anatomy, disfigured, deformed, mutation, mutilated, ugly, totem pole,(poorly drawn face), cloned face, several faces, long neck, mutated hands, bad hands, poorly drawn hands,extra limbs, malformed limbs, missing arms, missing fingers, extra fingers, fused fingers, too many fingers,missing legs, extra legs, malformed legs, extra digit, fewer digits, glitchy, cropped, jpeg artifacts, signature, watermark, username, text, error" #@param {type:"string"}
-n_samples = 4 #@param {type:"number"}
-scale = 7.5 #@param {type:"number"}
-timesteps = 50
-
-
-# Sometimes the nsfw checker is confused by the images, you can disable
-# it at your own risk here
-disable_safety = True
+  image = pipe(prompt +",　realistic, highly detailed, high quality", height=512, width=512, negative_prompt = "((low quality)),((poor quality)),((clone)),retro style, bad anatomy,((lowres)), blurry, (worst quality), ((low quality)), normal quality,bad anatomy, disfigured, deformed, mutation, mutilated, ugly, totem pole,(poorly drawn face), cloned face, several faces, long neck, mutated hands, bad hands, poorly drawn hands,extra limbs, malformed limbs, missing arms, missing fingers, extra fingers, fused fingers, too many fingers,missing legs, extra legs, malformed legs, extra digit, fewer digits, glitchy, cropped, jpeg artifacts, signature, watermark, username, text, errorretro style ,bad anatomy,((lowres)), blurry, (worst quality), normal quality,bad anatomy, disfigured, deformed, mutation, mutilated, ugly, totem pole,(poorly drawn face), cloned face, several faces, long neck, mutated hands, bad hands, poorly drawn hands,extra limbs, malformed limbs, missing arms, missing fingers, extra fingers, fused fingers, too many fingers,missing legs, extra legs, malformed legs, extra digit, fewer digits, glitchy, cropped, jpeg artifacts, signature, watermark, username, text, error", guidance_scale = 7.5,num_inference_steps = 50).images[0]
+    
+  image.save("sd_image.png")
 
-if disable_safety:
-  def null_safety(images, **kwargs):
-      return images, False
-  pipe.safety_checker = null_safety
+  return image
 
-with autocast("cuda"):
-  images = pipe(n_samples*[prompt], guidance_scale=scale,num_inference_steps=timesteps).images
+pipe = StableDiffusionPipeline.from_pretrained("Fung804/makoto-shinkai-v2", torch_dtype=torch.float16)  
+pipe = pipe.to("cuda")    
+generate = gr.Interface(fn = txt2img, inputs="text",outputs="image",allow_flagging="never")
 
-for idx, im in enumerate(images):
-  im.save(f"{idx:06}.png")
+generate.launch()