Save prediction result

samgeo/samgeo2.py

@@ -1090,6 +1090,7 @@ def set_video(
             raise ValueError("Input video_path must be a string.")
 
         self.video_path = output_dir
+        self._num_images = len(os.listdir(output_dir))
         self.inference_state = self.predictor.init_state(video_path=output_dir)
 
     def predict_video(
@@ -1105,6 +1106,27 @@ def predict_video(
             output_dir (Optional[str]): The directory to save the output images. Defaults to None.
             img_ext (str): The file extension for the output images. Defaults to "png".
         """
+
+        from PIL import Image
+
+        def save_image_from_dict(data, output_path="output_image.png"):
+            # Find the shape of the first array in the dictionary (assuming all arrays have the same shape)
+            array_shape = next(iter(data.values())).shape[1:]
+
+            # Initialize an empty array with the same shape as the arrays in the dictionary, filled with zeros
+            output_array = np.zeros(array_shape, dtype=np.uint8)
+
+            # Iterate over each key and array in the dictionary
+            for key, array in data.items():
+                # Assign the key value wherever the boolean array is True
+                output_array[array[0]] = key
+
+            # Convert the output array to a PIL image
+            image = Image.fromarray(output_array)
+
+            # Save the image
+            image.save(output_path)
+
         prompts = self._convert_prompts(prompts)
         predictor = self.predictor
         inference_state = self.inference_state
@@ -1121,6 +1143,13 @@ def predict_video(
             )
 
         video_segments = {}
+        num_frames = self._num_images
+        num_digits = len(str(num_frames))
+
+        if output_dir is not None:
+            if not os.path.exists(output_dir):
+                os.makedirs(output_dir)
+
         for out_frame_idx, out_obj_ids, out_mask_logits in predictor.propagate_in_video(
             inference_state
         ):
@@ -1129,10 +1158,16 @@ def predict_video(
                 for i, out_obj_id in enumerate(out_obj_ids)
             }
 
+            if output_dir is not None:
+                output_path = os.path.join(
+                    output_dir, f"{str(out_frame_idx).zfill(num_digits)}.{img_ext}"
+                )
+                save_image_from_dict(video_segments[out_frame_idx], output_path)
+
         self.video_segments = video_segments
 
-        if output_dir is not None:
-            self.save_video_segments(output_dir, img_ext)
+        # if output_dir is not None:
+        #     self.save_video_segments(output_dir, img_ext)
 
     def save_video_segments(self, output_dir: str, img_ext: str = "png") -> None:
         """Save the video segments to the output directory.