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README.md

@@ -1,10 +1,10 @@
 ---
 title: Lucy Text To Image
-emoji: 📈
-colorFrom: gray
-colorTo: yellow
+emoji: 💃
+colorFrom: blue
+colorTo: pink
 sdk: gradio
-sdk_version: 3.44.4
+sdk_version: 3.44.3
 app_file: app.py
 pinned: false
 ---

app.py

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+import gradio as gr
+import torch
+from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
+
+import numpy as np
+import os
+import cv2
+from PIL import Image, ImageDraw
+import insightface
+from insightface.app import FaceAnalysis
+
+# Diffusion
+model_base = "runwayml/stable-diffusion-v1-5"
+
+pipe = StableDiffusionPipeline.from_pretrained(model_base, torch_dtype=torch.float16, use_safetensors=True, safety_checker=None,)
+pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+
+lora_model_path = "./loralucy3/checkpoint-95000"
+pipe.unet.load_attn_procs(lora_model_path)
+pipe.to("cuda")
+
+
+# Insightface model
+app = FaceAnalysis(name='buffalo_l')
+app.prepare(ctx_id=0, det_size=(640, 640))
+
+
+def face_swap(src_img, dest_img):
+    src_img = Image.open('./images/' + src_img + '.JPG')
+    
+    # Convert to RGB
+    src_img = src_img.convert(mode='RGB')
+    dest_img = dest_img.convert(mode='RGB')
+
+    # Convert to array
+    src_img_arr = np.asarray(src_img)
+    dest_img_arr = np.asarray(dest_img)
+
+    # Face detection
+    src_faces = app.get(src_img_arr)
+    dest_faces = app.get(dest_img_arr)
+
+    # Initialize swapper
+    swapper = insightface.model_zoo.get_model('inswapper_128.onnx', download=False, download_zip=False)
+
+    # Swap face
+    res = dest_img_arr.copy()
+    for face in dest_faces:
+    	res = swapper.get(res, face, src_faces[0], paste_back=True)
+
+    # Convert to PIL image
+    final_image = Image.fromarray(np.uint8(res)).convert('RGB')
+
+    return final_image 
+
+
+def greet(description,color,features,occasion,type_,face):
+
+    # Parse input
+    prompt = 'white background '
+    description = 'description:' + description.replace(' ', '-')
+    color = ' color:' + ','.join(color)
+    features = ' features:' + ','.join(features)
+    occasion = ' occasion:' + ','.join(occasion)
+    type_ = ' type:' + ','.join(type_)
+   
+    prompt += description + color + features +  occasion + type_
+
+    print('prompt:',prompt)
+    image = pipe(
+        prompt,
+        negative_prompt='deformed face,bad anatomy',
+        width=312,
+        height=512,
+        num_inference_steps=100,
+        guidance_scale=7.5,
+        cross_attention_kwargs={"scale": 1.0}
+        ).images[0]
+
+    if(face != 'Normal'):
+        image = face_swap(face, image)
+    
+    return image
+
+iface = gr.Interface(fn=greet, 
+                     inputs=[gr.Textbox(label='Description'),
+                            gr.Dropdown(label='Color',choices=['Beige','Black','Blue','Brown','Green','Grey','Orange','Pink','Purple','Red','White','Yellow'],multiselect=True),
+                            gr.Dropdown(label='Features',choices=['3/4-sleeve','Babydoll','Closed-Back','Corset','Crochet','Cutouts','Draped','Floral','Gloves','Halter','Lace','Long','Long-Sleeve','Midi','No-Slit','Off-The-Shoulder','One-Shoulder','Open-Back','Pockets','Print','Puff-Sleeve','Ruched','Satin','Sequins','Shimmer','Short','Short-Sleeve','Side-Slit','Square-Neck','Strapless','Sweetheart-Neck','Tight','V-Neck','Velvet','Wrap'],multiselect=True),
+                            gr.Dropdown(label='Occasion',choices=['Homecoming','Casual','Wedding-Guest','Festival','Sorority','Day','Vacation','Summer','Pool-Party','Birthday','Date-Night','Party','Holiday','Winter-Formal','Valentines-Day','Prom','Graduation'],multiselect=True),
+                            gr.Dropdown(label='Type',choices=['Mini-Dresses','Midi-Dresses','Maxi-Dresses','Two-Piece-Sets','Rompers','Jeans','Jumpsuits','Pants','Tops','Jumpers/Cardigans','Skirts','Shorts','Bodysuits','Swimwear'],multiselect=True),
+                            gr.Dropdown(label='Face',choices=['Normal','Cat','Lisa','Mila'], value='Normal'),
+                            ], 
+                     outputs=gr.Image(type="pil", label="Final Image", width=312, height=512))
+iface.launch()

inswapper_128.onnx

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+\cb3   --resolution=\cf6 \strokec6 512\cf0 \strokec4  --random_flip \\\cb1 \
+\cb3   --train_batch_size=\cf6 \strokec6 1\cf0 \strokec4  \\\cb1 \
+\cb3   --num_train_epochs=\cf6 \strokec6 20\cf0 \strokec4  --checkpointing_steps=\cf6 \strokec6 5000\cf0 \strokec4  \\\cb1 \
+\cb3   --learning_rate=\cf6 \strokec6 1e-04\cf0 \strokec4  --lr_scheduler=\cf5 \strokec5 "constant"\cf0 \strokec4  --lr_warmup_steps=\cf6 \strokec6 0\cf0 \strokec4  \\\cb1 \
+\cb3   --seed=\cf6 \strokec6 42\cf0 \strokec4  \\\cb1 \
+\cb3   --output_dir=model_name \\\cb1 \
+\cb3   --validation_prompt=\cf5 \strokec5 "description:Foxie-Floral-Sequin-Tulle-Dress-in-White"\cf0 \cb1 \strokec4 \
+}