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Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -1,840 +1,35 @@
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import gradio as gr
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import spaces
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import replicate
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import os
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import
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from
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import time
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import tempfile
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import base64
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import numpy as np
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import gc
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os.environ['REPLICATE_API_TOKEN'] = os.getenv('REPLICATE_API_TOKEN')
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# --- Helper Functions ---
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def get_with_retry(url, max_retries=3, timeout=60):
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"""URL 요청을 재시도 로직과 함께 처리"""
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for i in range(max_retries):
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try:
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response = requests.get(url, timeout=timeout)
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if response.status_code == 200:
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return response
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except requests.exceptions.Timeout:
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if i == max_retries - 1:
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raise
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time.sleep(2) # 재시도 전 대기
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except Exception as e:
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if i == max_retries - 1:
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raise
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time.sleep(2)
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return None
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def validate_image_size(image, max_size=2048):
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"""이미지 크기 검증 및 리사이즈"""
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if image is None:
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return None
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if image.width > max_size or image.height > max_size:
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ratio = min(max_size/image.width, max_size/image.height)
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new_size = (int(image.width * ratio), int(image.height * ratio))
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image = image.resize(new_size, Image.LANCZOS)
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return image
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# --- Outpainting Functions ---
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def can_expand(source_width, source_height, target_width, target_height, alignment):
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"""Checks if the image can be expanded based on the alignment."""
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if alignment in ("Left", "Right") and source_width >= target_width:
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return False
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if alignment in ("Top", "Bottom") and source_height >= target_height:
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return False
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return True
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def prepare_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom):
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"""Prepares the image with white margins and creates a mask for outpainting."""
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target_size = (width, height)
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# Calculate the scaling factor to fit the image within the target size
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scale_factor = min(target_size[0] / image.width, target_size[1] / image.height)
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new_width = int(image.width * scale_factor)
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new_height = int(image.height * scale_factor)
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# Resize the source image to fit within target size
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source = image.resize((new_width, new_height), Image.LANCZOS)
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# Apply resize option using percentages
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if resize_option == "Full":
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resize_percentage = 100
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elif resize_option == "50%":
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resize_percentage = 50
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elif resize_option == "33%":
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resize_percentage = 33
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elif resize_option == "25%":
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resize_percentage = 25
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else: # Custom
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resize_percentage = custom_resize_percentage
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# Calculate new dimensions based on percentage
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resize_factor = resize_percentage / 100
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new_width = int(source.width * resize_factor)
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new_height = int(source.height * resize_factor)
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# Ensure minimum size of 64 pixels
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new_width = max(new_width, 64)
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new_height = max(new_height, 64)
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# Resize the image
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source = source.resize((new_width, new_height), Image.LANCZOS)
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# Calculate the overlap in pixels based on the percentage
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overlap_x = int(new_width * (overlap_percentage / 100))
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overlap_y = int(new_height * (overlap_percentage / 100))
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# Ensure minimum overlap of 1 pixel
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overlap_x = max(overlap_x, 1)
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overlap_y = max(overlap_y, 1)
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# Calculate margins based on alignment
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if alignment == "Middle":
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margin_x = (target_size[0] - new_width) // 2
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margin_y = (target_size[1] - new_height) // 2
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elif alignment == "Left":
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margin_x = 0
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margin_y = (target_size[1] - new_height) // 2
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elif alignment == "Right":
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margin_x = target_size[0] - new_width
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margin_y = (target_size[1] - new_height) // 2
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elif alignment == "Top":
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margin_x = (target_size[0] - new_width) // 2
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margin_y = 0
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elif alignment == "Bottom":
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margin_x = (target_size[0] - new_width) // 2
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margin_y = target_size[1] - new_height
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# Adjust margins to eliminate gaps
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margin_x = max(0, min(margin_x, target_size[0] - new_width))
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margin_y = max(0, min(margin_y, target_size[1] - new_height))
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# Create a new background image with white margins and paste the resized source image
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background = Image.new('RGB', target_size, (255, 255, 255))
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background.paste(source, (margin_x, margin_y))
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# Create the mask
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mask = Image.new('L', target_size, 255)
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mask_draw = ImageDraw.Draw(mask)
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# Calculate overlap areas
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white_gaps_patch = 2
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left_overlap = margin_x + overlap_x if overlap_left else margin_x + white_gaps_patch
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right_overlap = margin_x + new_width - overlap_x if overlap_right else margin_x + new_width - white_gaps_patch
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top_overlap = margin_y + overlap_y if overlap_top else margin_y + white_gaps_patch
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bottom_overlap = margin_y + new_height - overlap_y if overlap_bottom else margin_y + new_height - white_gaps_patch
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if alignment == "Left":
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left_overlap = margin_x + overlap_x if overlap_left else margin_x
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elif alignment == "Right":
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right_overlap = margin_x + new_width - overlap_x if overlap_right else margin_x + new_width
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elif alignment == "Top":
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top_overlap = margin_y + overlap_y if overlap_top else margin_y
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elif alignment == "Bottom":
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bottom_overlap = margin_y + new_height - overlap_y if overlap_bottom else margin_y + new_height
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# Draw the mask
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mask_draw.rectangle([
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(left_overlap, top_overlap),
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(right_overlap, bottom_overlap)
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], fill=0)
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return background, mask
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def preview_outpaint(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom):
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"""Creates a preview showing the mask overlay for outpainting."""
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if not image:
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return None
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background, mask = prepare_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom)
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# Create a preview image showing the mask
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preview = background.copy().convert('RGBA')
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# Create a semi-transparent red overlay
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red_overlay = Image.new('RGBA', background.size, (255, 0, 0, 64)) # Reduced alpha to 64 (25% opacity)
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# Convert black pixels in the mask to semi-transparent red
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red_mask = Image.new('RGBA', background.size, (0, 0, 0, 0))
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red_mask.paste(red_overlay, (0, 0), mask)
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# Overlay the red mask on the background
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preview = Image.alpha_composite(preview, red_mask)
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return preview
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# --- Image Upload Functions ---
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def upload_image_to_hosting(image):
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"""
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Upload image to multiple hosting services with fallback
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"""
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try:
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#
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image.save(buffered, format="PNG")
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buffered.seek(0)
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img_base64 = base64.b64encode(buffered.getvalue()).decode()
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response = requests.post(
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"https://api.imgbb.com/1/upload",
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data={
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'key': '6d207e02198a847aa98d0a2a901485a5',
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'image': img_base64,
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},
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timeout=30
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)
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if response.status_code == 200:
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data = response.json()
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if data.get('success'):
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return data['data']['url']
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except:
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pass
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try:
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# Method 2: Try 0x0.st (simple and reliable)
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buffered = BytesIO()
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image.save(buffered, format="PNG")
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buffered.seek(0)
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files = {'file': ('image.png', buffered, 'image/png')}
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response = requests.post("https://0x0.st", files=files, timeout=30)
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if response.status_code == 200:
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return response.text.strip()
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except:
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pass
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# Method 3: Fallback to base64
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buffered = BytesIO()
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image.save(buffered, format="PNG")
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buffered.seek(0)
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img_base64 = base64.b64encode(buffered.getvalue()).decode()
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return f"data:image/png;base64,{img_base64}"
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@spaces.GPU(duration=90)
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def upscale_image(image):
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"""
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Upscale the generated image using Real-ESRGAN (mandatory)
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"""
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if not image:
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return None, "No image to upscale"
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if not os.getenv('REPLICATE_API_TOKEN'):
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return None, "Please set REPLICATE_API_TOKEN"
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start_time = time.time()
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try:
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# 시간 체크
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if time.time() - start_time > 80:
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return image, "Time limit approaching, returning original image"
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# Upload image to hosting
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image_url = upload_image_to_hosting(image)
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input={
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"image": image_url,
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"scale": 4 # 4x upscaling as default
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}
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)
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#
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if isinstance(output, str):
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output_url = output
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elif isinstance(output, list) and len(output) > 0:
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output_url = output[0]
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elif hasattr(output, 'url'):
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output_url = output.url()
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return img, "🔍 Upscaled 4x successfully!"
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# Try direct read if available
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if hasattr(output, 'read'):
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img_data = output.read()
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img = Image.open(BytesIO(img_data))
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gc.collect()
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return img, "🔍 Upscaled 4x successfully!"
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return None, "Could not process upscaled output"
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except spaces.GPUError as e:
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gc.collect()
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return image, "GPU resources exhausted, returning original image"
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except Exception as e:
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gc.collect()
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return image, f"Upscale error (returning original): {str(e)[:50]}"
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def apply_outpainting_to_image(image, outpaint_prompt, target_width, target_height,
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overlap_percentage, resize_option, custom_resize_percentage,
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alignment, overlap_left, overlap_right, overlap_top, overlap_bottom):
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"""
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Apply outpainting to an image by preparing it with white margins
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"""
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if not image:
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return None
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# Check if expansion is possible
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if not can_expand(image.width, image.height, target_width, target_height, alignment):
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alignment = "Middle"
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# Prepare the image with white margins for outpainting
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outpaint_image, mask = prepare_image_and_mask(
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image, target_width, target_height, overlap_percentage,
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resize_option, custom_resize_percentage, alignment,
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overlap_left, overlap_right, overlap_top, overlap_bottom
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)
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return outpaint_image
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@spaces.GPU(duration=180)
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def process_images(prompt, image1, image2=None, enable_outpaint=False, outpaint_prompt="",
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target_width=1280, target_height=720, overlap_percentage=10,
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resize_option="Full", custom_resize_percentage=50,
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alignment="Middle", overlap_left=True, overlap_right=True,
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overlap_top=True, overlap_bottom=True, progress=gr.Progress()):
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"""
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Process uploaded images with Replicate API, apply optional outpainting, and mandatory upscaling
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"""
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if not image1:
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return None, "Please upload at least one image"
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if not os.getenv('REPLICATE_API_TOKEN'):
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return None, "Please set REPLICATE_API_TOKEN"
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start_time = time.time()
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try:
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progress(0.1, desc="Validating images...")
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# Validate and resize images if needed
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image1 = validate_image_size(image1)
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if image2:
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image2 = validate_image_size(image2)
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# Time check
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if time.time() - start_time > 170:
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return None, "Processing time exceeded. Please try with smaller images."
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progress(0.2, desc="Preparing images...")
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# Step 1: Apply outpainting if enabled
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if enable_outpaint:
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# Apply outpainting to image1
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image1 = apply_outpainting_to_image(
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image1, outpaint_prompt, target_width, target_height,
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overlap_percentage, resize_option, custom_resize_percentage,
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alignment, overlap_left, overlap_right, overlap_top, overlap_bottom
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)
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# Apply outpainting to image2 if it exists
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if image2:
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image2 = apply_outpainting_to_image(
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image2, outpaint_prompt, target_width, target_height,
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overlap_percentage, resize_option, custom_resize_percentage,
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alignment, overlap_left, overlap_right, overlap_top, overlap_bottom
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)
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# Update the prompt if outpainting is enabled
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if outpaint_prompt:
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prompt = f"replace the white margins. {outpaint_prompt}. {prompt}"
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progress(0.3, desc="Uploading to server...")
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# Step 2: Upload images and process with Nano Banana
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image_urls = []
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url1 = upload_image_to_hosting(image1)
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image_urls.append(url1)
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if image2:
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url2 = upload_image_to_hosting(image2)
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image_urls.append(url2)
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# Time check
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if time.time() - start_time > 170:
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return None, "Processing time exceeded during upload."
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progress(0.5, desc="Generating image...")
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# Run the Nano Banana model
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output = replicate.run(
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"google/nano-banana",
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input={
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"prompt": prompt,
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"image_input": image_urls
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}
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)
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if output is None:
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return None, "No output received"
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# Clear intermediate variables
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del image_urls
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gc.collect()
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progress(0.7, desc="Processing output...")
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# Get the generated image with retry logic
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generated_image = None
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# Try different methods to get the output
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output_url = None
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if isinstance(output, str):
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output_url = output
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elif isinstance(output, list) and len(output) > 0:
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output_url = output[0]
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elif hasattr(output, 'url'):
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output_url = output.url()
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|
410 |
-
if output_url:
|
411 |
-
response = get_with_retry(output_url, max_retries=3, timeout=60)
|
412 |
-
if response and response.status_code == 200:
|
413 |
-
generated_image = Image.open(BytesIO(response.content))
|
414 |
-
|
415 |
-
# Try direct read if available
|
416 |
-
if not generated_image and hasattr(output, 'read'):
|
417 |
-
img_data = output.read()
|
418 |
-
generated_image = Image.open(BytesIO(img_data))
|
419 |
-
|
420 |
-
if not generated_image:
|
421 |
-
return None, "Could not process output"
|
422 |
-
|
423 |
-
# Clear output variable
|
424 |
-
del output
|
425 |
-
gc.collect()
|
426 |
-
|
427 |
-
# Time check before upscaling
|
428 |
-
if time.time() - start_time > 170:
|
429 |
-
return generated_image, "✨ Generated (time limit reached, skipping upscale)"
|
430 |
-
|
431 |
-
progress(0.8, desc="Upscaling image...")
|
432 |
-
|
433 |
-
# Step 3: Apply mandatory upscaling
|
434 |
-
upscaled_image, upscale_status = upscale_image(generated_image)
|
435 |
-
|
436 |
-
# Clear generated image from memory
|
437 |
-
del generated_image
|
438 |
-
gc.collect()
|
439 |
-
|
440 |
-
progress(1.0, desc="Complete!")
|
441 |
-
|
442 |
-
if upscaled_image:
|
443 |
-
return upscaled_image, f"✨ Generated and {upscale_status}"
|
444 |
-
else:
|
445 |
-
# If upscaling fails, return the generated image with a warning
|
446 |
-
return generated_image, "✨ Generated (upscaling failed, returning original)"
|
447 |
-
|
448 |
-
except spaces.GPUError as e:
|
449 |
-
gc.collect()
|
450 |
-
return None, "GPU resources exhausted. Please try again later."
|
451 |
-
except requests.exceptions.Timeout:
|
452 |
-
gc.collect()
|
453 |
-
return None, "Request timeout. Please try with smaller images."
|
454 |
except Exception as e:
|
455 |
-
|
456 |
-
|
457 |
-
|
458 |
-
gc.collect() # Final cleanup
|
459 |
-
|
460 |
-
def toggle_outpaint_options(enable):
|
461 |
-
"""Toggle visibility of outpainting options"""
|
462 |
-
return gr.update(visible=enable)
|
463 |
-
|
464 |
-
def preload_presets(target_ratio):
|
465 |
-
"""Updates the width and height based on the selected aspect ratio."""
|
466 |
-
if target_ratio == "9:16":
|
467 |
-
return 720, 1280
|
468 |
-
elif target_ratio == "16:9":
|
469 |
-
return 1280, 720
|
470 |
-
elif target_ratio == "1:1":
|
471 |
-
return 1024, 1024
|
472 |
-
else: # Custom
|
473 |
-
return 1280, 720
|
474 |
-
|
475 |
-
def toggle_custom_resize_slider(resize_option):
|
476 |
-
return gr.update(visible=(resize_option == "Custom"))
|
477 |
-
|
478 |
-
# Enhanced CSS with modern, minimal design
|
479 |
-
css = """
|
480 |
-
.gradio-container {
|
481 |
-
background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
|
482 |
-
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
|
483 |
-
min-height: 100vh;
|
484 |
-
}
|
485 |
-
.header-container {
|
486 |
-
background: linear-gradient(135deg, #ffd93d 0%, #ffb347 100%);
|
487 |
-
padding: 2.5rem;
|
488 |
-
border-radius: 24px;
|
489 |
-
margin-bottom: 2.5rem;
|
490 |
-
box-shadow: 0 20px 60px rgba(255, 179, 71, 0.25);
|
491 |
-
}
|
492 |
-
.logo-text {
|
493 |
-
font-size: 3.5rem;
|
494 |
-
font-weight: 900;
|
495 |
-
color: #2d3436;
|
496 |
-
text-align: center;
|
497 |
-
margin: 0;
|
498 |
-
letter-spacing: -2px;
|
499 |
-
}
|
500 |
-
.subtitle {
|
501 |
-
color: #2d3436;
|
502 |
-
text-align: center;
|
503 |
-
font-size: 1rem;
|
504 |
-
margin-top: 0.5rem;
|
505 |
-
opacity: 0.8;
|
506 |
-
}
|
507 |
-
.main-content {
|
508 |
-
background: rgba(255, 255, 255, 0.95);
|
509 |
-
backdrop-filter: blur(20px);
|
510 |
-
border-radius: 24px;
|
511 |
-
padding: 2.5rem;
|
512 |
-
box-shadow: 0 10px 40px rgba(0, 0, 0, 0.08);
|
513 |
-
}
|
514 |
-
.gr-button-primary {
|
515 |
-
background: linear-gradient(135deg, #ffd93d 0%, #ffb347 100%) !important;
|
516 |
-
border: none !important;
|
517 |
-
color: #2d3436 !important;
|
518 |
-
font-weight: 700 !important;
|
519 |
-
font-size: 1.1rem !important;
|
520 |
-
padding: 1.2rem 2rem !important;
|
521 |
-
border-radius: 14px !important;
|
522 |
-
transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
|
523 |
-
text-transform: uppercase;
|
524 |
-
letter-spacing: 1px;
|
525 |
-
width: 100%;
|
526 |
-
margin-top: 1rem !important;
|
527 |
-
}
|
528 |
-
.gr-button-primary:hover {
|
529 |
-
transform: translateY(-3px) !important;
|
530 |
-
box-shadow: 0 15px 40px rgba(255, 179, 71, 0.35) !important;
|
531 |
-
}
|
532 |
-
.gr-button-secondary {
|
533 |
-
background: linear-gradient(135deg, #74b9ff 0%, #0984e3 100%) !important;
|
534 |
-
border: none !important;
|
535 |
-
color: white !important;
|
536 |
-
font-weight: 600 !important;
|
537 |
-
font-size: 0.95rem !important;
|
538 |
-
padding: 0.8rem 1.5rem !important;
|
539 |
-
border-radius: 12px !important;
|
540 |
-
transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
|
541 |
-
}
|
542 |
-
.gr-button-secondary:hover {
|
543 |
-
transform: translateY(-2px) !important;
|
544 |
-
box-shadow: 0 10px 30px rgba(9, 132, 227, 0.3) !important;
|
545 |
-
}
|
546 |
-
.gr-input, .gr-textarea {
|
547 |
-
background: #ffffff !important;
|
548 |
-
border: 2px solid #e1e8ed !important;
|
549 |
-
border-radius: 14px !important;
|
550 |
-
color: #2d3436 !important;
|
551 |
-
font-size: 1rem !important;
|
552 |
-
padding: 0.8rem 1rem !important;
|
553 |
-
}
|
554 |
-
.gr-input:focus, .gr-textarea:focus {
|
555 |
-
border-color: #ffd93d !important;
|
556 |
-
box-shadow: 0 0 0 4px rgba(255, 217, 61, 0.15) !important;
|
557 |
-
}
|
558 |
-
.gr-form {
|
559 |
-
background: transparent !important;
|
560 |
-
border: none !important;
|
561 |
-
}
|
562 |
-
.gr-panel {
|
563 |
-
background: #ffffff !important;
|
564 |
-
border: 2px solid #e1e8ed !important;
|
565 |
-
border-radius: 16px !important;
|
566 |
-
padding: 1.5rem !important;
|
567 |
-
}
|
568 |
-
.gr-box {
|
569 |
-
border-radius: 14px !important;
|
570 |
-
border-color: #e1e8ed !important;
|
571 |
-
}
|
572 |
-
label {
|
573 |
-
color: #636e72 !important;
|
574 |
-
font-weight: 600 !important;
|
575 |
-
font-size: 0.85rem !important;
|
576 |
-
text-transform: uppercase;
|
577 |
-
letter-spacing: 0.5px;
|
578 |
-
margin-bottom: 0.5rem !important;
|
579 |
-
}
|
580 |
-
.status-text {
|
581 |
-
font-family: 'SF Mono', 'Monaco', monospace;
|
582 |
-
color: #00b894;
|
583 |
-
font-size: 0.9rem;
|
584 |
-
}
|
585 |
-
.image-container {
|
586 |
-
border-radius: 14px !important;
|
587 |
-
overflow: hidden;
|
588 |
-
border: 2px solid #e1e8ed !important;
|
589 |
-
background: #fafbfc !important;
|
590 |
-
}
|
591 |
-
.preview-container {
|
592 |
-
border: 2px dashed #ff6b6b !important;
|
593 |
-
border-radius: 14px !important;
|
594 |
-
padding: 1rem !important;
|
595 |
-
background: rgba(255, 107, 107, 0.05) !important;
|
596 |
-
}
|
597 |
-
footer {
|
598 |
-
display: none !important;
|
599 |
-
}
|
600 |
-
/* Equal sizing for all image containers */
|
601 |
-
.image-upload {
|
602 |
-
min-height: 200px !important;
|
603 |
-
max-height: 200px !important;
|
604 |
-
}
|
605 |
-
.output-image {
|
606 |
-
min-height: 420px !important;
|
607 |
-
max-height: 420px !important;
|
608 |
-
}
|
609 |
-
/* Ensure consistent spacing */
|
610 |
-
.gr-row {
|
611 |
-
gap: 1rem !important;
|
612 |
-
}
|
613 |
-
.gr-column {
|
614 |
-
gap: 1rem !important;
|
615 |
-
}
|
616 |
-
/* Outpainting options styling */
|
617 |
-
.outpaint-section {
|
618 |
-
background: rgba(116, 185, 255, 0.1) !important;
|
619 |
-
border: 2px solid #74b9ff !important;
|
620 |
-
border-radius: 14px !important;
|
621 |
-
padding: 1rem !important;
|
622 |
-
margin-top: 1rem !important;
|
623 |
-
}
|
624 |
-
"""
|
625 |
-
|
626 |
-
with gr.Blocks(css=css, theme=gr.themes.Base()) as demo:
|
627 |
-
with gr.Column(elem_classes="header-container"):
|
628 |
-
gr.HTML("""
|
629 |
-
<h1 class="logo-text">🍌 Nano Banana PRO</h1>
|
630 |
-
<p class="subtitle">AI-Powered Image Style Transfer with Outpainting & Auto-Upscaling(X4)</p>
|
631 |
-
<div style="display: flex; justify-content: center; align-items: center; gap: 10px; margin-top: 20px;">
|
632 |
-
<a href="https://ginigen.com" target="_blank">
|
633 |
-
<img src="https://img.shields.io/static/v1?label=ginigen&message=special%20ai%20sERVICE&color=%230000ff&labelColor=%23800080&logo=google&logoColor=white&style=for-the-badge" alt="badge">
|
634 |
-
</a>
|
635 |
-
|
636 |
-
<a href="https://discord.gg/openfreeai" target="_blank">
|
637 |
-
<img src="https://img.shields.io/static/v1?label=Discord&message=Openfree%20AI&color=%230000ff&labelColor=%23800080&logo=discord&logoColor=white&style=for-the-badge" alt="Discord Openfree AI">
|
638 |
-
</a>
|
639 |
-
</div>
|
640 |
-
""")
|
641 |
-
|
642 |
-
with gr.Column(elem_classes="main-content"):
|
643 |
-
with gr.Row(equal_height=True):
|
644 |
-
# Left Column - Inputs
|
645 |
-
with gr.Column(scale=1):
|
646 |
-
prompt = gr.Textbox(
|
647 |
-
label="Style Description",
|
648 |
-
placeholder="Describe your style...",
|
649 |
-
lines=3,
|
650 |
-
value="Make the sheets in the style of the logo. Make the scene natural.",
|
651 |
-
elem_classes="prompt-input"
|
652 |
-
)
|
653 |
-
|
654 |
-
with gr.Row(equal_height=True):
|
655 |
-
image1 = gr.Image(
|
656 |
-
label="Primary Image",
|
657 |
-
type="pil",
|
658 |
-
height=200,
|
659 |
-
elem_classes="image-container image-upload"
|
660 |
-
)
|
661 |
-
image2 = gr.Image(
|
662 |
-
label="Secondary Image (Optional)",
|
663 |
-
type="pil",
|
664 |
-
height=200,
|
665 |
-
elem_classes="image-container image-upload"
|
666 |
-
)
|
667 |
-
|
668 |
-
# Outpainting Options
|
669 |
-
enable_outpaint = gr.Checkbox(
|
670 |
-
label="🎨 Enable Outpainting (Expand Image)",
|
671 |
-
value=False
|
672 |
-
)
|
673 |
-
|
674 |
-
with gr.Column(visible=False, elem_classes="outpaint-section") as outpaint_options:
|
675 |
-
outpaint_prompt = gr.Textbox(
|
676 |
-
label="Outpaint Prompt",
|
677 |
-
placeholder="Describe what should appear in the extended areas",
|
678 |
-
value="extend the image naturally",
|
679 |
-
lines=2
|
680 |
-
)
|
681 |
-
|
682 |
-
with gr.Row():
|
683 |
-
target_ratio = gr.Radio(
|
684 |
-
label="Target Ratio",
|
685 |
-
choices=["9:16", "16:9", "1:1", "Custom"],
|
686 |
-
value="16:9"
|
687 |
-
)
|
688 |
-
alignment_dropdown = gr.Dropdown(
|
689 |
-
choices=["Middle", "Left", "Right", "Top", "Bottom"],
|
690 |
-
value="Middle",
|
691 |
-
label="Alignment"
|
692 |
-
)
|
693 |
-
|
694 |
-
with gr.Row():
|
695 |
-
target_width = gr.Slider(
|
696 |
-
label="Target Width",
|
697 |
-
minimum=512,
|
698 |
-
maximum=2048,
|
699 |
-
step=8,
|
700 |
-
value=1280
|
701 |
-
)
|
702 |
-
target_height = gr.Slider(
|
703 |
-
label="Target Height",
|
704 |
-
minimum=512,
|
705 |
-
maximum=2048,
|
706 |
-
step=8,
|
707 |
-
value=720
|
708 |
-
)
|
709 |
-
|
710 |
-
with gr.Accordion("Advanced Outpaint Settings", open=False):
|
711 |
-
overlap_percentage = gr.Slider(
|
712 |
-
label="Mask overlap (%)",
|
713 |
-
minimum=1,
|
714 |
-
maximum=50,
|
715 |
-
value=10,
|
716 |
-
step=1,
|
717 |
-
info="Controls the blending area"
|
718 |
-
)
|
719 |
-
|
720 |
-
with gr.Row():
|
721 |
-
overlap_top = gr.Checkbox(label="Overlap Top", value=True)
|
722 |
-
overlap_right = gr.Checkbox(label="Overlap Right", value=True)
|
723 |
-
with gr.Row():
|
724 |
-
overlap_left = gr.Checkbox(label="Overlap Left", value=True)
|
725 |
-
overlap_bottom = gr.Checkbox(label="Overlap Bottom", value=True)
|
726 |
-
|
727 |
-
with gr.Row():
|
728 |
-
resize_option = gr.Radio(
|
729 |
-
label="Resize input image",
|
730 |
-
choices=["Full", "50%", "33%", "25%", "Custom"],
|
731 |
-
value="Full"
|
732 |
-
)
|
733 |
-
custom_resize_percentage = gr.Slider(
|
734 |
-
label="Custom resize (%)",
|
735 |
-
minimum=1,
|
736 |
-
maximum=100,
|
737 |
-
step=1,
|
738 |
-
value=50,
|
739 |
-
visible=False
|
740 |
-
)
|
741 |
-
|
742 |
-
preview_outpaint_btn = gr.Button(
|
743 |
-
"👁️ Preview Outpaint Mask",
|
744 |
-
variant="secondary"
|
745 |
-
)
|
746 |
-
|
747 |
-
generate_btn = gr.Button(
|
748 |
-
"Generate Magic with Auto-Upscale ✨",
|
749 |
-
variant="primary",
|
750 |
-
size="lg"
|
751 |
-
)
|
752 |
-
|
753 |
-
# Right Column - Output
|
754 |
-
with gr.Column(scale=1):
|
755 |
-
output_image = gr.Image(
|
756 |
-
label="Generated & Upscaled Result",
|
757 |
-
type="pil",
|
758 |
-
height=420,
|
759 |
-
elem_classes="image-container output-image"
|
760 |
-
)
|
761 |
-
|
762 |
-
status = gr.Textbox(
|
763 |
-
label="Status",
|
764 |
-
interactive=False,
|
765 |
-
lines=1,
|
766 |
-
elem_classes="status-text",
|
767 |
-
value="Ready to generate..."
|
768 |
-
)
|
769 |
-
|
770 |
-
outpaint_preview = gr.Image(
|
771 |
-
label="Outpaint Preview (red area will be generated)",
|
772 |
-
type="pil",
|
773 |
-
visible=False,
|
774 |
-
elem_classes="preview-container"
|
775 |
-
)
|
776 |
-
|
777 |
-
gr.Markdown("""
|
778 |
-
### 📌 Features:
|
779 |
-
- **Style Transfer**: Apply artistic styles to your images
|
780 |
-
- **Outpainting** (Optional): Expand your images with AI
|
781 |
-
- **Auto 4x Upscaling**: All outputs are automatically upscaled for maximum quality
|
782 |
-
- **Optimized for ZeroGPU**: Improved stability and reduced timeout issues
|
783 |
-
|
784 |
-
### 💡 Tips:
|
785 |
-
- Upload 1-2 images to apply style transfer
|
786 |
-
- Enable outpainting to expand image boundaries
|
787 |
-
- All generated images are automatically upscaled 4x
|
788 |
-
- Large images are automatically resized for optimal processing
|
789 |
-
""")
|
790 |
-
|
791 |
-
# Event handlers
|
792 |
-
enable_outpaint.change(
|
793 |
-
fn=toggle_outpaint_options,
|
794 |
-
inputs=[enable_outpaint],
|
795 |
-
outputs=[outpaint_options]
|
796 |
-
)
|
797 |
-
|
798 |
-
target_ratio.change(
|
799 |
-
fn=preload_presets,
|
800 |
-
inputs=[target_ratio],
|
801 |
-
outputs=[target_width, target_height]
|
802 |
-
)
|
803 |
-
|
804 |
-
resize_option.change(
|
805 |
-
fn=toggle_custom_resize_slider,
|
806 |
-
inputs=[resize_option],
|
807 |
-
outputs=[custom_resize_percentage]
|
808 |
-
)
|
809 |
-
|
810 |
-
preview_outpaint_btn.click(
|
811 |
-
fn=preview_outpaint,
|
812 |
-
inputs=[
|
813 |
-
image1, target_width, target_height, overlap_percentage,
|
814 |
-
resize_option, custom_resize_percentage, alignment_dropdown,
|
815 |
-
overlap_left, overlap_right, overlap_top, overlap_bottom
|
816 |
-
],
|
817 |
-
outputs=[outpaint_preview]
|
818 |
-
).then(
|
819 |
-
fn=lambda: gr.update(visible=True),
|
820 |
-
outputs=[outpaint_preview]
|
821 |
-
)
|
822 |
-
|
823 |
-
generate_btn.click(
|
824 |
-
fn=process_images,
|
825 |
-
inputs=[
|
826 |
-
prompt, image1, image2, enable_outpaint, outpaint_prompt,
|
827 |
-
target_width, target_height, overlap_percentage,
|
828 |
-
resize_option, custom_resize_percentage, alignment_dropdown,
|
829 |
-
overlap_left, overlap_right, overlap_top, overlap_bottom
|
830 |
-
],
|
831 |
-
outputs=[output_image, status]
|
832 |
-
)
|
833 |
|
834 |
-
# Launch
|
835 |
if __name__ == "__main__":
|
836 |
-
|
837 |
-
share=True,
|
838 |
-
server_name="0.0.0.0",
|
839 |
-
server_port=7860
|
840 |
-
)
|
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|
1 |
import os
|
2 |
+
import sys
|
3 |
+
import streamlit as st
|
4 |
+
from tempfile import NamedTemporaryFile
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5 |
|
6 |
+
def main():
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|
7 |
try:
|
8 |
+
# Get the code from secrets
|
9 |
+
code = os.environ.get("MAIN_CODE")
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10 |
|
11 |
+
if not code:
|
12 |
+
st.error("⚠️ The application code wasn't found in secrets. Please add the MAIN_CODE secret.")
|
13 |
+
return
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|
14 |
|
15 |
+
# Create a temporary Python file
|
16 |
+
with NamedTemporaryFile(suffix='.py', delete=False, mode='w') as tmp:
|
17 |
+
tmp.write(code)
|
18 |
+
tmp_path = tmp.name
|
19 |
|
20 |
+
# Execute the code
|
21 |
+
exec(compile(code, tmp_path, 'exec'), globals())
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22 |
|
23 |
+
# Clean up the temporary file
|
24 |
+
try:
|
25 |
+
os.unlink(tmp_path)
|
26 |
+
except:
|
27 |
+
pass
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28 |
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|
29 |
except Exception as e:
|
30 |
+
st.error(f"⚠️ Error loading or executing the application: {str(e)}")
|
31 |
+
import traceback
|
32 |
+
st.code(traceback.format_exc())
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|
33 |
|
|
|
34 |
if __name__ == "__main__":
|
35 |
+
main()
|
|
|
|
|
|
|
|