diff --git a/src/satextractor/scheduler/scheduler.py b/src/satextractor/scheduler/scheduler.py
index 2a6027d..7d8f545 100644
--- a/src/satextractor/scheduler/scheduler.py
+++ b/src/satextractor/scheduler/scheduler.py
@@ -115,106 +115,111 @@ def create_tasks_by_splits(
     items = []
     tasks: List[ExtractionTask] = []
 
-    with open(item_collection, "rb") as json_file:
-        for item in ijson.items(json_file, "features.item"):
-            if counter != collection_chunks:
-                items.append(item)
-                counter += 1
-            else:
-                counter = 0
-
-                stac_items = pystac.ItemCollection(
-                    items=[pystac.Item.from_dict(item) for item in items],
+    if isinstance(item_collection, str):
+        json_file = open(item_collection, "rb")
+        all_items = ijson.items(json_file, "features.item")
+    else:
+        all_items = item_collection["features"]
+
+    for item in all_items:
+        if counter < collection_chunks:
+            items.append(item)
+            counter += 1
+        else:
+            counter = 0
+
+            stac_items = pystac.ItemCollection(
+                items=[pystac.Item.from_dict(it) for it in items],
+            )
+            gdf = gpd.GeoDataFrame.from_features(
+                {"type": "FeatureCollection", "features": items},
+            )
+            items = []
+
+            gdf.datetime = pd.to_datetime(gdf.datetime).dt.tz_localize(None)
+
+            tiles_gdf = cluster_tiles_in_utm(tiles, split_m)
+
+            logger.info(
+                "Creating extraction tasks for each constellations, date, and band ...",
+            )
+
+            task_tracker = 0
+
+            for constellation in constellations:
+
+                # Get all the date ranges for the given interval
+                dates = get_dates_in_range(
+                    gdf.loc[gdf.constellation == constellation, "datetime"]
+                    .min()
+                    .to_pydatetime(),
+                    gdf.loc[gdf.constellation == constellation, "datetime"]
+                    .max()
+                    .to_pydatetime(),
+                    interval,
                 )
-                gdf = gpd.GeoDataFrame.from_features(
-                    {"type": "FeatureCollection", "features": items},
-                )
-                items = []
-
-                gdf.datetime = pd.to_datetime(gdf.datetime).dt.tz_localize(None)
 
-                tiles_gdf = cluster_tiles_in_utm(tiles, split_m)
+                if bands is not None:
+                    run_bands = [
+                        b["band"].name
+                        for kk, b in BAND_INFO[constellation].items()
+                        if b["band"].name in bands
+                    ]
+                else:
+                    run_bands = [
+                        b["band"].name for kk, b in BAND_INFO[constellation].items()
+                    ]
 
                 logger.info(
-                    "Creating extraction tasks for each constellations, date, and band ...",
+                    f"Getting cluster item indexes for {constellation} in parallel...",
                 )
-
-                task_tracker = 0
-
-                for constellation in constellations:
-
-                    # Get all the date ranges for the given interval
-                    dates = get_dates_in_range(
-                        gdf.loc[gdf.constellation == constellation, "datetime"]
-                        .min()
-                        .to_pydatetime(),
-                        gdf.loc[gdf.constellation == constellation, "datetime"]
-                        .max()
-                        .to_pydatetime(),
-                        interval,
-                    )
-
-                    if bands is not None:
-                        run_bands = [
-                            b["band"].name
-                            for kk, b in BAND_INFO[constellation].items()
-                            if b["band"].name in bands
-                        ]
-                    else:
-                        run_bands = [
-                            b["band"].name for kk, b in BAND_INFO[constellation].items()
-                        ]
-
-                    logger.info(
-                        f"Getting cluster item indexes for {constellation} in parallel...",
-                    )
-                    with tqdm_joblib(
-                        tqdm(desc="Extraction Tasks creation.", total=len(dates)),
-                    ):
-                        cluster_items = Parallel(n_jobs=n_jobs, verbose=verbose)(
-                            delayed(get_cluster_items_indexes)(
-                                gdf[
-                                    (gdf.datetime >= start)
-                                    & (gdf.datetime <= end)
-                                    & (gdf.constellation == constellation)
-                                ],
-                                tiles_gdf,
-                            )
-                            for start, end in dates
+                with tqdm_joblib(
+                    tqdm(desc="Extraction Tasks creation.", total=len(dates)),
+                ):
+                    cluster_items = Parallel(n_jobs=n_jobs, verbose=verbose)(
+                        delayed(get_cluster_items_indexes)(
+                            gdf[
+                                (gdf.datetime >= start)
+                                & (gdf.datetime <= end)
+                                & (gdf.constellation == constellation)
+                            ],
+                            tiles_gdf,
                         )
+                        for start, end in dates
+                    )
 
-                    for i, date_cluster_item in enumerate(cluster_items):
-                        for k, v in date_cluster_item.items():
-                            if v:
-                                c_tiles = tiles_gdf[tiles_gdf["cluster_id"] == k]
-                                c_items_geom = gdf.iloc[v].unary_union
-                                t_indexes = c_tiles[
-                                    c_tiles.geometry.apply(c_items_geom.contains)
-                                ].index
-                                if not t_indexes.empty:
-                                    c_items = pystac.ItemCollection(
-                                        [
-                                            stac_items.items[item_index]
-                                            for item_index in v
-                                        ],
+                for i, date_cluster_item in enumerate(cluster_items):
+                    for k, v in date_cluster_item.items():
+                        if v:
+                            c_tiles = tiles_gdf[tiles_gdf["cluster_id"] == k]
+                            c_items_geom = gdf.iloc[v].unary_union
+                            t_indexes = c_tiles[
+                                c_tiles.geometry.apply(c_items_geom.contains)
+                            ].index
+                            if not t_indexes.empty:
+                                c_items = pystac.ItemCollection(
+                                    [stac_items.items[item_index] for item_index in v],
+                                )
+                                region_tiles = [tiles[t_index] for t_index in t_indexes]
+                                sensing_time = dates[i][0]
+
+                                for b in run_bands:
+                                    tasks.append(
+                                        ExtractionTask(
+                                            task_id=str(task_tracker),
+                                            tiles=region_tiles,
+                                            item_collection=c_items,
+                                            band=b,
+                                            constellation=constellation,
+                                            sensing_time=sensing_time,
+                                        ),
                                     )
-                                    region_tiles = [
-                                        tiles[t_index] for t_index in t_indexes
-                                    ]
-                                    sensing_time = dates[i][0]
-
-                                    for b in run_bands:
-                                        tasks.append(
-                                            ExtractionTask(
-                                                task_id=str(task_tracker),
-                                                tiles=region_tiles,
-                                                item_collection=c_items,
-                                                band=b,
-                                                constellation=constellation,
-                                                sensing_time=sensing_time,
-                                            ),
-                                        )
-                                        task_tracker += 1
+                                    task_tracker += 1
+
+    try:
+        json_file.close()
+    except Exception:
+        pass
 
     logger.info(f"There are a total of {len(tasks)} tasks")