Upload sdxl_thumbsup.py

sdxl_thumbsup.py

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+# -*- coding: utf-8 -*-
+"""SDXL-Thumbsup.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1T0tqXsscUsDxLSt6MIiqEmNVYEuCejGL
+
+# Training DreamBooth LoRA with Stable Diffusion XL on Trump Thumbs Up Images:
+
+## Linking Drive
+"""
+
+from google.colab import drive
+drive.mount('/content/drive')
+
+import warnings
+warnings.filterwarnings("ignore")
+
+"""## Installing & Login to Hugging Face
+
+"""
+
+!pip install huggingface-hub
+
+!git config --global credential.helper store
+
+!huggingface-cli login
+
+"""##Cloning Hugging Face/diffusers - [Repo](https://github.com/huggingface/diffusers)
+
+"""
+
+import os
+import subprocess
+
+
+subprocess.run(["git", "clone", "https://github.com/huggingface/diffusers"])
+os.chdir("diffusers")
+subprocess.run(["pip", "install", "-e", "."])
+
+"""## Installing Requirements - Dreambooth SDXL"""
+
+os.chdir("examples/dreambooth")
+
+!pip install -r requirements_sdxl.txt
+
+"""## Write Basic Configuration for Accelerate"""
+
+from accelerate.utils import write_basic_config
+write_basic_config()
+
+"""##  Load and Display Images from Drive"""
+
+import os
+import cv2
+from matplotlib import pyplot as plt
+
+dir = '/content/drive/MyDrive/SDXL/Images/thumbsup'
+count = 0
+max_images = 10
+
+for img_name in os.listdir(dir):
+    img_path = os.path.join(dir, img_name)
+
+    if img_path.lower().endswith(('.png', '.jpg', '.jpeg')):
+        img = cv2.imread(img_path)
+
+        if img is None:
+            print(f"Failed to load image: {img_path}")
+            continue
+
+        img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+
+        plt.imshow(img)
+        plt.axis('off')
+        plt.show()
+
+        count += 1
+        if count >= max_images:
+            break
+
+"""## Installing Required Libraries"""
+
+!pip install tensorrt bitsandbytes xformers wandb
+
+pip install --upgrade diffusers accelerate
+
+"""## Logging into Weights and Biases"""
+
+!wandb login
+
+"""## Train DreamBooth LoRA Model with Stable Diffusion XL"""
+
+!accelerate launch train_dreambooth_lora_sdxl.py \
+  --pretrained_model_name_or_path="stabilityai/stable-diffusion-xl-base-1.0" \
+  --instance_data_dir="/content/drive/MyDrive/SDXL/Images/thumbsup" \
+  --pretrained_vae_model_name_or_path="stabilityai/sdxl-vae" \
+  --output_dir="/content/drive/MyDrive/SDXL/Output-Complex" \
+  --mixed_precision="fp16" \
+  --instance_prompt="a high-quality photo of Trump showing thumbs up" \
+  --resolution=1024 \
+  --train_batch_size=1 \
+  --gradient_accumulation_steps=2 \
+  --learning_rate=2e-4 \
+  --lr_scheduler="constant_with_warmup" \
+  --lr_warmup_steps=0 \
+  --max_train_steps=500 \
+  --validation_prompt="A high-quality photo of Trump showing thumbs up in a taco restaurant, detailed, sharp focus" \
+  --validation_epochs=15 \
+  --seed="42" \
+  --push_to_hub \
+  --gradient_checkpointing \
+  --checkpointing_steps=100 \
+  --use_8bit_adam \
+  --prior_loss_weight=0.8 \
+  --num_class_images=10 \
+  --report_to="wandb"
+
+# Commented out IPython magic to ensure Python compatibility.
+# %cd ..
+
+!pip uninstall diffusers
+!pip install -e ./diffusers
+
+"""## Load LoRA Weights and Generate Images
+
+"""
+
+from huggingface_hub.repocard import RepoCard
+from diffusers import DiffusionPipeline
+import torch
+
+pipeline = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16)
+pipeline = pipeline.to("cuda")
+pipeline.load_lora_weights("/content/diffusers/examples/dreambooth/pytorch_lora_weights.safetensors")
+
+image = pipeline("A high quality picture of Trump showing the thumbs up in Paris", num_inference_steps=50).images[0]
+
+image_path = "/content/drive/MyDrive/SDXL/Output-Complex/Trump1.png"
+image.save(image_path)
+
+print("Image saved at:", image_path)
+
+image = pipeline("A picture of Trump showing the thumbs up as a Anime character, detailed, sharp focus", num_inference_steps=50).images[0]
+
+image_path = "/content/drive/MyDrive/SDXL/Output-Complex/Trump2.png"
+image.save(image_path)
+
+print("Image saved at:", image_path)
+
+image = pipeline("A picture of Trump showing thumbsup in whitehouse", num_inference_steps=50).images[0]
+
+image_path = "/content/drive/MyDrive/SDXL/Output-Complex/Trump3.png"
+image.save(image_path)
+
+print("Image saved at:", image_path)
+
+image = pipeline("A high quality picture of Trump showing the thumbs up as The Statue of Liberty", num_inference_steps=50).images[0]
+
+image_path = "/content/drive/MyDrive/SDXL/Output-Complex/Trump4.png"
+image.save(image_path)
+
+print("Image saved at:", image_path)
+
+image = pipeline("A high quality picture of Trump showing thumbs up in a lake with a laptop", num_inference_steps=50).images[0]
+
+image_path = "/content/drive/MyDrive/SDXL/Output-Complex/Trump5.png"
+image.save(image_path)
+
+print("Image saved at:", image_path)
+
+"""## Push to Hugging Face Hub"""
+
+from huggingface_hub import HfApi
+
+api = HfApi()
+
+username = "Paresh1879"
+repo_name = "stable-diffusion-xl-thumbsup-extend"
+
+api.upload_folder(repo_id=f"{username}/{repo_name}", folder_path="/content/drive/MyDrive/SDXL")