Spaces:
Runtime error
Runtime error
| 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) |