Create app.py

app.py

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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
+
+
+'''
+Here we are using a pretrained 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=='.tif':
+    #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)
+
+    # 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'{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():
+          output = gr.outputs.File("zip")
+  source_image_loader.click(get_shape_files,img_source,output)
+my_app.launch(debug = True)