Rahatara's picture
Rename app.py to appv1.py
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import streamlit as st
from PIL import Image, ImageEnhance, ImageOps
import numpy as np
import io
import zipfile
def apply_basic_augmentations(image):
"""Applies basic augmentations such as rotation and color jitter."""
image = image.rotate(np.random.uniform(-30, 30))
enhancer = ImageEnhance.Color(image)
image = enhancer.enhance(np.random.uniform(0.75, 1.25))
if np.random.rand() > 0.5:
image = ImageOps.mirror(image)
return image
def simulate_latent_space_noising(image, noise_scale=25):
"""Simulates latent space manipulation by adding noise."""
image_array = np.array(image)
noise = np.random.normal(0, noise_scale, image_array.shape)
noised_image_array = np.clip(image_array + noise, 0, 255).astype(np.uint8)
return Image.fromarray(noised_image_array)
def augment_image(image, augmentations_count):
"""Generates augmented versions of a single image."""
augmented_images = []
for _ in range(augmentations_count):
augmented_image = apply_basic_augmentations(image)
augmented_image = simulate_latent_space_noising(augmented_image)
augmented_images.append(augmented_image)
return augmented_images
def create_downloadable_zip(augmented_images):
"""Creates a ZIP file in memory for downloading."""
zip_buffer = io.BytesIO()
with zipfile.ZipFile(zip_buffer, "a", zipfile.ZIP_DEFLATED, False) as zip_file:
for idx, image in enumerate(augmented_images):
img_byte_arr = io.BytesIO()
image.save(img_byte_arr, format="JPEG")
zip_file.writestr(f"augmented_image_{idx+1}.jpg", img_byte_arr.getvalue())
zip_buffer.seek(0)
return zip_buffer
st.title("Ready-To-Use Synthetic Image Dataset Generation with Few-shots")
uploaded_files = st.file_uploader("Choose images (1-10)", accept_multiple_files=True, type=["jpg", "jpeg", "png"])
augmentations_count = st.number_input("Number of augmented samples per image", min_value=1, max_value=10, value=3)
if uploaded_files:
all_augmented_images = []
for uploaded_file in uploaded_files:
image = Image.open(uploaded_file).convert("RGB")
augmented_images = augment_image(image, augmentations_count)
all_augmented_images.extend(augmented_images)
if st.button("Generate Synthetic Dataset") and all_augmented_images:
zip_buffer = create_downloadable_zip(all_augmented_images)
st.download_button(
label="Download ZIP",
data=zip_buffer,
file_name="augmented_images.zip",
mime="application/zip"
)