Delete app.py

app.py

@@ -1,75 +0,0 @@
-import gradio as gr
-import cv2
-import numpy as np
-from typing import Union, List
-from pathlib import Path
-from PIL import Image
-import torch
-
-# Function to resize images
-
-def resize_images(images, scale_percent=50):
-    resized_images = []
-    for img in images:
-        width = int(img.shape[1] * scale_percent / 100)
-        height = int(img.shape[0] * scale_percent / 100)
-        dim = (width, height)
-        resized = cv2.resize(img, dim, interpolation=cv2.INTER_AREA)
-        resized_images.append(resized)
-    return resized_images
-
-# Function to stitch images
-
-def stitch_images(image_paths, scale_percent=50):
-    images = [cv2.imread(path) for path in image_paths]
-    resized_images = resize_images(images, scale_percent)
-    stitcher = cv2.Stitcher_create()
-    status, stitched_image = stitcher.stitch(resized_images)
-
-    if status == cv2.Stitcher_OK:
-        print("Stitching successful!")
-        return stitched_image
-    else:
-        print(f"Stitching failed with status code: {status}")
-        return None
-
-# Main image processing function
-
-def process_image(image_paths, scale_percent=50):
-    stitched_image = stitch_images(image_paths, scale_percent)
-
-    if stitched_image is not None:
-        try:
-            stitched_image_rgb = cv2.cvtColor(stitched_image, cv2.COLOR_BGR2RGB)
-            return stitched_image_rgb
-        except Exception as e:
-            print(str(e))
-            return stitched_image
-
-# Gradio interface function
-
-def gradio_stitch_and_detect(image_files):
-    image_paths = [file.name for file in image_files]
-    result_image = process_image(image_paths, scale_percent=50)
-
-    if result_image is not None:
-        result_image_rgb = result_image
-        pil_image = Image.fromarray(result_image_rgb)
-        pil_image.save("stitched_image.jpg", "JPEG")
-        return pil_image, "stitched_image.jpg"
-
-    return None, None
-
-# Gradio interface
-with gr.Blocks() as interface:
-    gr.Markdown("<h1 style='color: #2196F3; text-align: center;'>Image Stitcher 🧵</h1>")
-    gr.Markdown("<h3 style='color: #2196F3; text-align: center;'>=== Upload the images (.jpg, .png, etc) you want to stitch ===</h3>")
-
-    image_upload = gr.Files(type="filepath", label="Upload Images")
-    stitch_button = gr.Button("Stitch", variant="primary")
-    stitched_image = gr.Image(type="pil", label="Stitched Image")
-    download_button = gr.File(label="Download Stitched Image")
-
-    stitch_button.click(gradio_stitch_and_detect, inputs=image_upload, outputs=[stitched_image, download_button])
-
-interface.launch()