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import gradio as gr
import numpy as np
import torch
import matplotlib.pyplot as plt
import cv2
import os
import leafmap
from samgeo import SamGeo, show_image, download_file, overlay_images, tms_to_geotiff
from zipfile import ZipFile
#initialize the model
sam = SamGeo(
model_type="vit_h",
checkpoint='sam_vit_h_4b8939.pth',
sam_kwargs=None,
)
def get_all_file_paths(directory):
# initializing empty file paths list
file_paths = []
# crawling through directory and subdirectories
for root, directories, files in os.walk(directory):
for filename in files:
# join the two strings in order to form the full filepath.
filepath = os.path.join(root, filename)
file_paths.append(filepath)
# returning all file paths
return file_paths
def get_shape_files(image):
filename, file_extension = os.path.splitext(image.name)
# print(filename,file_extension)
if file_extension in ['.tif','tiff']:
#mkdir for app
storage='app_store'
if os.path.exists(storage):
pass
else:
os.mkdir(storage)
zip_folder=f'{storage}/zip_folder'
if os.path.exists(zip_folder):
pass
else:
os.mkdir(zip_folder)
out_file=f'{storage}/out_files'
if os.path.exists(out_file):
pass
else:
os.mkdir(out_file)
# load_model()
sam.generate(image.name, output=f"{out_file}/masks.tif", foreground=True, unique=True)
sam.tiff_to_vector(f"{out_file}/masks.tif", out_file)
sam.show_anns(axis="off", alpha=1, output=f"{out_file}/annotations.tif")
#converting tif to jpg
image = cv2.imread(f"{out_file}/annotations.tif")
cv2.imwrite("{}/{}.jpg".format(out_file,'converted'), image)
# writing files to a zipfile
file_paths=get_all_file_paths(out_file)
# for file_name in file_paths:
# print(file_name)
with ZipFile(f'{zip_folder}/shapefile.zip','w') as zip:
# writing each file one by one
for file in file_paths:
zip.write(file)
print('All files zipped successfully!')
return f"{out_file}/converted.jpg",f'{zip_folder}/shapefile.zip'
# get_shape_files(image)
else:
return "Try uploading .tif file for processing!."
my_app = gr.Blocks()
with my_app:
gr.Markdown("<center><h1>Segmenting Satellite Image</h1></center>")
gr.Markdown("<center><h3>Processing time depends on the file size and since the instance is running on CPU it takes longer time.</h></center>")
with gr.TabItem("Get Shapefiles"):
with gr.Row():
with gr.Column():
img_source = gr.File(label="Please select source tif")
source_image_loader = gr.Button("Get Shape File")
with gr.Column():
image=gr.Image()
output = gr.outputs.File("zip")
source_image_loader.click(get_shape_files,img_source,[image,output])
my_app.launch(debug = True) |