Update app.py

app.py

@@ -17,27 +17,16 @@ from torch.multiprocessing import Pool as Pool
 #from diffusers.utils import export_to_gif
 #from huggingface_hub import hf_hub_download
 #from safetensors.torch import load_file
-from diffusers import DiffusionPipeline, StableDiffusionXLImg2ImgPipeline
+from diffusers import DiffusionPipeline
 from diffusers.utils import load_image
 #import jax
 #import jax.numpy as jnp
 
-def port_inc():
-    env = os.getenv("CUSTOM_PORT")
-    if env == None:
-        os.environ["CUSTOM_PORT"]="7860"
-    else:
-        os.environ["CUSTOM_PORT"]=str(int(env)+1)
-
 def pipe_t2i():
     PIPE = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16, token=os.getenv("hf_token")).to("cuda")
-    return PIPE
-    
-def pipe_i2i():
-    PIPE = DiffusionPipeline.from_pretrained("yisol/IDM-VTON", torch_dtype=torch.float16).to("cuda")
     PIPE.unet = torch.compile(PIPE.unet, mode="reduce-overhead", fullgraph=True)
     return PIPE
-
+    
 def translate(text,lang):
     if text == None or lang == None:
         return ""       
@@ -84,7 +73,7 @@ def generate_random_string(length):
     return ''.join(random.choice(characters) for _ in range(length))
 
 @spaces.GPU(duration=75)
-def Piper(name,name2,posi,neg):
+def Piper(name,posi):
     print("starting piper")
     
     ret1 = pp1(
@@ -96,15 +85,6 @@ def Piper(name,name2,posi,neg):
         guidance_scale=0
     )
     ret1.images[0].save(name)
-    
-    img = load_image(name).convert("RGB")
-    
-    ret2 = pp2(
-        prompt=posi,
-        negative_prompt=neg,
-        image=img
-    )
-    ret2.images[0].save(name2)
 
 def tok(pipe,txt):
     toks = pipe.tokenizer(txt)['input_ids']
@@ -154,28 +134,21 @@ def infer(p):
         print("infer: started")
     
         p1 = p["a"]
-        p2 = p["b"]
         name = generate_random_string(12)+".png"
-        name2 = "_"+name
 
         _do = ['beautiful', 'playful', 'photographed', 'realistic', 'dynamic poze', 'deep field', 'reasonable coloring', 'rough texture', 'best quality', 'focused']
         if p1 != "":
             _do.append(f'{p1}')
         posi = " ".join(_do)
 
-        neg = " "
-        if p2 != "":
-            neg = f'{p2} where in {p1}'
-        
-        Piper(name,name2,posi,neg)
+        Piper(name,posi)
     
-        return name2
+        return name
 
-def run(p1,p2,*result):
+def run(p1,*result):
     
         p1_en = translate(p1,"english")
-        p2_en = translate(p2,"english")
-        p = {"a":p1_en,"b":p2_en}
+        p = {"a":p1_en}
         ln = len(result)
         print("images: "+str(ln))
         rng = list(range(ln))
@@ -193,11 +166,9 @@ def main():
 
     global result
     global pp1
-    global pp2
 
     result=[]
     pp1=pipe_t2i()
-    pp2=pipe_i2i()
 
     mp.set_start_method("fork", force=True)
     
@@ -209,14 +180,7 @@ def main():
             with gr.Row():
                 prompt = gr.Textbox(
                     elem_id="prompt",
-                    placeholder="INCLUDE",
-                    container=False,
-                    max_lines=1
-                )
-            with gr.Row():
-                prompt2 = gr.Textbox(
-                    elem_id="prompt2",
-                    placeholder="EXCLUDE",
+                    placeholder="KEYWORDS",
                     container=False,
                     max_lines=1
                 )
@@ -225,8 +189,9 @@ def main():
             with gr.Row():
                 result.append(gr.Image(interactive=False,elem_classes="image-container", label="Result", show_label=False, type='filepath', show_share_button=False))
                 result.append(gr.Image(interactive=False,elem_classes="image-container", label="Result", show_label=False, type='filepath', show_share_button=False))
+                result.append(gr.Image(interactive=False,elem_classes="image-container", label="Result", show_label=False, type='filepath', show_share_button=False))
 
-        run_button.click(fn=run,inputs=[prompt,prompt2,*result],outputs=result)
+        run_button.click(fn=run,inputs=[prompt,*result],outputs=result)
         demo.queue().launch()
 
 if __name__ == "__main__":