File size: 4,205 Bytes
88eaee2 11fb33c 88eaee2 11fb33c 88eaee2 11fb33c 88eaee2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 |
import gradio as gr
import cv2
import numpy as np
# from panorama import stitch_images
def process_images(image_files, crop, y_start, y_end, x_start, x_end):
if not image_files:
return "No images uploaded.", None
# Extract the first element of each tuple if it's a tuple
extracted_images = []
for item in image_files:
if isinstance(item, tuple):
# If item is (img, None), extract 'img' only
img = item[0]
else:
# If for some reason it's not a tuple, assume it's already the image
img = item
# Check if img is not None and is a numpy array
if img is not None and isinstance(img, np.ndarray):
extracted_images.append(img)
# If after extraction no valid images found
if not extracted_images:
return "No valid images found for stitching.", None
try:
# Define crop coordinates
if crop:
crop_coords = (int(y_start), int(y_end), int(x_start), int(x_end))
else:
crop_coords = None
# Initialize OpenCV's Stitcher
stitcher = cv2.Stitcher_create()
# Perform stitching
status, panorama = stitcher.stitch(extracted_images)
if status != cv2.Stitcher_OK:
raise RuntimeError(f"Stitching failed with status code {status}.")
if crop:
y_start, y_end, x_start, x_end = crop_coords
cropped_panorama = panorama[y_start:y_end, x_start:x_end]
return panorama, cropped_panorama
return panorama, None
except Exception as e:
# Raise a gradio Error to avoid returning image outputs as text
raise gr.Error(f"Error during stitching: {str(e)}")
# Define Gradio interface using Blocks for better layout control
with gr.Blocks(title="Creating Panorama using OpenCV") as demo:
gr.Markdown("# Creating Panorama using OpenCV")
gr.Markdown("Upload the series of images sequentially and get the perfect Panorama!")
with gr.Row(equal_height=True):
examples = [
"./scene/scene1.jpg",
"./scene/scene2.jpg",
"./scene/scene3.jpg",
"./scene/scene4.jpg",
"./scene/scene5.jpg",
"./scene/scene6.jpg",
"./scene/scene7.jpg",
"./scene/scene8.jpg",
]
with gr.Column():
image_upload = gr.Gallery(
value=examples,
columns=4,
label="Upload Images",
file_types=["image"],
format="jpeg",
type="numpy",
)
crop_checkbox = gr.Checkbox(label="Apply Cropping to Panorama", value=False)
with gr.Row():
y_start = gr.Number(label="Crop Y Start", value=90, interactive=True)
y_end = gr.Number(label="Crop Y End", value=867, interactive=True)
with gr.Row():
x_start = gr.Number(label="Crop X Start", value=1, interactive=True)
x_end = gr.Number(label="Crop X End", value=2000, interactive=True)
stitch_button = gr.Button("Stitch Images")
with gr.Row():
with gr.Column():
stitched_output = gr.Image(label="Stitched Panorama")
cropped_output = gr.Image(label="Cropped Panorama")
# Disable cropping input fields if checkbox is not selected
def toggle_crop_inputs(crop):
return gr.update(visible=crop), gr.update(visible=crop), gr.update(visible=crop), gr.update(visible=crop)
crop_checkbox.change(fn=toggle_crop_inputs, inputs=[crop_checkbox], outputs=[y_start, y_end, x_start, x_end])
# Define the button click event
stitch_button.click(
fn=process_images,
inputs=[image_upload, crop_checkbox, y_start, y_end, x_start, x_end],
outputs=[stitched_output, cropped_output],
)
gr.Markdown(
"""
**Note**:
- Ensure that the uploaded images have overlapping regions for successful stitching.
- Cropping coordinates should be within the dimensions of the stitched panorama.
"""
)
# Launch the Gradio interface
demo.launch(show_error=True)
|