Image Rotation

.gitmodules

@@ -1,3 +1,9 @@
 [submodule "anchor/third_party/ace"]
 	path = anchor/third_party/ace
 	url = https://github.com/Mickmcginnis/ace
+[submodule "anchor/third_party/Zero-DCE"]
+	path = anchor/third_party/Zero-DCE
+	url = [email protected]:Li-Chongyi/Zero-DCE.git
+[submodule "anchor/third_party/zero_dce"]
+	path = anchor/third_party/zero_dce
+	url = [email protected]:ayushchakra/zero_dce.git

anchor/backend/data/ace.py

@@ -353,12 +353,19 @@ def process_training_data(
         firebase_processed_tar_path: str = str(
             Path(combined_path).parent.parent / f"processedTrainingTars/{tar_name}"
         )
-        downloader.delete_file((Path(firebase_tar_queue_path) / tar_name).as_posix())
-        downloader.upload_file(
-            remote_location=firebase_processed_tar_path,
-            local_location=downloader.local_tar_location,
-        )
-        print("[INFO]: Moved tar from tarQueue to processedTars directory in firebase")
+        try:
+            downloader.delete_file(
+                (Path(firebase_tar_queue_path) / tar_name).as_posix()
+            )
+            downloader.upload_file(
+                remote_location=firebase_processed_tar_path,
+                local_location=downloader.local_tar_location,
+            )
+            print(
+                "[INFO]: Moved tar from tarQueue to processedTars directory in firebase"
+            )
+        except:
+            print("[WARNING] Unable to Move tar")
 
 
 @dataclass
@@ -396,12 +403,12 @@ def process_testing_data(
     prepare_ace_data(downloader.extracted_data)
     os.chdir(Path(__file__).parent.parent.parent / "third_party/ace")
     extracted_ace_folder = downloader.local_extraction_location / "ace"
-    model_name = Path(combined_path).stem.split("training_")[-1]
-    model_name = "_".join(model_name.split("_")[2:])
 
     if model_data_folder:
         model_weights_path = model_data_folder / "model.pt"
     else:
+        model_name = Path(combined_path).stem.split("training_")[-1]
+        model_name = "_".join(model_name.split("_")[2:])
         for dir, _, _ in os.walk(downloader.root_download_dir):
             dir_path = Path(dir)
             if str(dir_path).endswith(model_name) and dir_path.parts[-1].startswith(
@@ -434,14 +441,17 @@ def process_testing_data(
         tars = list_tars()
 
     # tars = ["training_ua-7c140933b99a14568ee768781fb5c9b2_ayush_mar_4_5_combined"]
-    tars = [
-        # 9:30
-        "testing_FE49EDB3-4A95-4B60-A942-5E41463DAEEF_ayush_mar_3.tar",
-        # 12:00
-        "testing_7AAC6056-FEA5-4712-8134-26B13499316C_ayush_mar_3.tar",
-        # Days later
-        "testing_2E4723D2-57C7-4AA1-B3B3-CE276ABF0DC7_ayush_mar_3.tar",
-    ]
+    # tars = [
+    #     "training_ua-7c140933b99a14568ee768781fb5c9b2_ayush_mar_4_5_combined_better_enhancement",
+    #     "training_ua-7c140933b99a14568ee768781fb5c9b2_ayush_mar_4_better_enhancement",
+    #     "training_ua-1bab71c5f9279e0777539be4abd6ae2b_ayush_mar_5_better_enhancement",
+    #     # # 9:30
+    #     # "testing_FE49EDB3-4A95-4B60-A942-5E41463DAEEF_ayush_mar_3",
+    #     # # 12:00
+    #     # "testing_7AAC6056-FEA5-4712-8134-26B13499316C_ayush_mar_3",
+    #     # # Days later
+    #     # "testing_2E4723D2-57C7-4AA1-B3B3-CE276ABF0DC7_ayush_mar_3",
+    # ]
 
     print("Processing: \n" + "\n".join(tars))
 

anchor/backend/data/extracted.py

@@ -141,6 +141,7 @@ def match_all_sensor(self):
         for phase in self.sensors_extracted:
             for sensor in self.sensors_extracted[phase]:
                 if sensor not in ["video", "april_tags", "google_cloud_anchor"]:
+                    breakpoint()
                     self.match_given_sensor(phase, sensor)
 
     def transform_poses_in_global_frame(self):

anchor/backend/data/firebase.py

@@ -22,20 +22,28 @@ def list_tars():
         FirebaseDownloader.initialized = True
     bucket = storage.bucket(FirebaseDownloader.firebase_bucket_name)
     # database = db.reference(url="https://stepnavigation-default-rtdb.firebaseio.com/")
-    # breakpoint()
-    tar_queue = "iosLoggerDemo/processedTrainingTars/"
-    tars = bucket.list_blobs(prefix=tar_queue)
-
     tar_names = []
+    # tar_queue = "iosLoggerDemo/processedTrainingTars/"
+    # tars = bucket.list_blobs(prefix=tar_queue)
 
-    for tar in tars:
-        if tar.name.endswith(".tar") and "ayush_mar_" in tar.name:
-            tar_names.append(tar.name)
 
-    tar_queue = "iosLoggerDemo/processedTestTars/"
+    # for tar in tars:
+    #     if tar.name.endswith(".tar") and "ayush_mar_" in tar.name:
+    #         tar_names.append(tar.name)
+
+    # tar_queue = "iosLoggerDemo/processedTestTars/"
+    # tars = bucket.list_blobs(prefix=tar_queue)
+    # for tar in tars:
+    #     if tar.name.endswith(".tar") and "ayush_mar_" in tar.name:
+    #         tar_names.append(tar.name)
+
+    tar_queue = "iosLoggerDemo/tarQueue/"
     tars = bucket.list_blobs(prefix=tar_queue)
     for tar in tars:
-        if tar.name.endswith(".tar") and "ayush_mar_" in tar.name:
+        if (
+            tar.name.endswith(".tar")
+            and "ayush_april_3" in tar.name
+        ):
             tar_names.append(tar.name)
 
     return tar_names
@@ -120,7 +128,7 @@ def extract_ios_logger_tar(self) -> Path:
             )
 
         # extract the videos by phase (test videos will not have mapping data so they need to be handled separately)
-        if str(self.local_tar_location).endswith("_combined"):
+        if "combined" in str(self.local_tar_location):
             self.combine_extract_ios_logger_video(mapping_phase=False)
             self.combine_extract_ios_logger_video(mapping_phase=True)
             self.combine_extract_intrinsics(mapping_phase=False)

anchor/backend/data/multi_model_ace.py

@@ -10,21 +10,21 @@
 import google
 
 combined_model_name = (
-    "training_ua-7c140933b99a14568ee768781fb5c9b2_ayush_mar_4_5_combined"
+    "training_ua-7c140933b99a14568ee768781fb5c9b2_ayush_mar_4_5_combined_better_enhancement"
 )
 individual_model_names = [
-    "training_ua-7c140933b99a14568ee768781fb5c9b2_ayush_mar_4",
-    "training_ua-1bab71c5f9279e0777539be4abd6ae2b_ayush_mar_5",
+    "training_ua-7c140933b99a14568ee768781fb5c9b2_ayush_mar_4_better_enhancement",
+    "training_ua-1bab71c5f9279e0777539be4abd6ae2b_ayush_mar_5_better_enhancement",
 ]
 test_datasets = [
     # 9:30
-    "testing_FE49EDB3-4A95-4B60-A942-5E41463DAEEF_ayush_mar_3.tar",
+    "testing_FE49EDB3-4A95-4B60-A942-5E41463DAEEF_ayush_mar_3_better_enhancement",
     # 12:00
-    "testing_7AAC6056-FEA5-4712-8134-26B13499316C_ayush_mar_3.tar",
+    "testing_7AAC6056-FEA5-4712-8134-26B13499316C_ayush_mar_3_better_enhancement",
     # Days later
-    "testing_2E4723D2-57C7-4AA1-B3B3-CE276ABF0DC7_ayush_mar_3.tar",
+    "testing_2E4723D2-57C7-4AA1-B3B3-CE276ABF0DC7_ayush_mar_3_better_enhancement",
 ]
-OUTPUT_BASE_DIR = Path(__file__).parent / ".cache/multi_model_results"
+OUTPUT_BASE_DIR = Path(__file__).parent / ".cache/better_enhancement_multi_model_results"
 
 
 def send_localization_request(
@@ -152,6 +152,9 @@ def main2():
                 Path(__file__).parent / f".cache/firebase_data/{model_name}/ace",
             )
 
+        if not OUTPUT_BASE_DIR.exists():
+            os.mkdir(OUTPUT_BASE_DIR)
+
         output_dir = OUTPUT_BASE_DIR / test_name.rstrip(".tar")
         if not output_dir.exists():
             os.mkdir(output_dir)

anchor/backend/eval/run_eval.py

@@ -1,7 +1,7 @@
 from pathlib import Path
 import json
-from utils.error import compute_rotational_error, compute_translation_error
-from utils.data_models import (
+from anchor.backend.eval.utils.error import compute_rotational_error, compute_translation_error
+from anchor.backend.eval.utils.data_models import (
     TestInfo,
     MapTestInfo,
     FrameData,
@@ -25,16 +25,16 @@
 }
 MULTI_MODEL_TEST_MAPPINGS = {
     # 9:30
-    1: "testing_2E4723D2-57C7-4AA1-B3B3-CE276ABF0DC7_ayush_mar_3",
+    1: "testing_2E4723D2-57C7-4AA1-B3B3-CE276ABF0DC7_ayush_mar_3_better_enhancement",
     # 12:00
-    2: "testing_7AAC6056-FEA5-4712-8134-26B13499316C_ayush_mar_3",
+    2: "testing_7AAC6056-FEA5-4712-8134-26B13499316C_ayush_mar_3_better_enhancement",
     # Days later
-    3: "testing_FE49EDB3-4A95-4B60-A942-5E41463DAEEF_ayush_mar_3",
+    3: "testing_FE49EDB3-4A95-4B60-A942-5E41463DAEEF_ayush_mar_3_better_enhancement",
 }
 MULTI_MODEL_TEST_METADATA_MAPPINGS = {
-    "testing_2E4723D2-57C7-4AA1-B3B3-CE276ABF0DC7_ayush_mar_3": "9:30 PM",
-    "testing_7AAC6056-FEA5-4712-8134-26B13499316C_ayush_mar_3": "12:00 PM",
-    "testing_FE49EDB3-4A95-4B60-A942-5E41463DAEEF_ayush_mar_3": "9:30 PM (Days Later)",
+    "testing_2E4723D2-57C7-4AA1-B3B3-CE276ABF0DC7_ayush_mar_3_better_enhancement": "9:30 PM",
+    "testing_7AAC6056-FEA5-4712-8134-26B13499316C_ayush_mar_3_better_enhancement": "12:00 PM",
+    "testing_FE49EDB3-4A95-4B60-A942-5E41463DAEEF_ayush_mar_3_better_enhancement": "9:30 PM (Days Later)",
 }
 FIGURE_DIR = Path(__file__).parent / "imgs"
 
@@ -245,7 +245,7 @@ def frame_bar_chart(dataset_name: str, visualize: bool, save: bool, smooth_ace:
 def analyze_multi_model_datasets(dataset_name, visualize: bool, save: bool):
     data_file = (
         Path(__file__).parent.parent
-        / "data/.cache/multi_model_results"
+        / "data/.cache/better_enhancement_multi_model_results"
         / dataset_name
         / "results.json"
     )
@@ -262,8 +262,50 @@ def analyze_multi_model_datasets(dataset_name, visualize: bool, save: bool):
 
     mm_analyzer = MultiModelAnalysis(results)
 
-    fig = plt.figure()
+    # data_file = (
+    #     Path(__file__).parent.parent
+    #     / "data/.cache/multi_model_results"
+    #     / dataset_name.strip("_better_enhancement")
+    #     / "results.json"
+    # )
+    # with open(data_file, "r") as file:
+    #     results = json.load(file)
+
+    # for model_name, data in results.items():
+    #     results[model_name] = TestDatum(
+    #         frames=[FrameData(**args) for args in data],
+    #         root_dir=Path(__file__).parent.parent
+    #         / "data/.cache/firebase_data"
+    #         / model_name.strip("_better_enhancement"),
+    #     )
+
+    # other_analyzer = MultiModelAnalysis(results)
+    # delta_trans_model0 = {}
+    # delta_trans_model1 = {}
+    # delta_num_model0 = {}
+    # delta_num_model1 = {}
+    # for key in mm_analyzer.model0_avg_translation_errs:
+    #     delta_trans_model0[key] = mm_analyzer.model0_avg_translation_errs[key] - other_analyzer.model0_avg_translation_errs[key]
+    #     delta_trans_model1[key] = mm_analyzer.model1_avg_translation_errs[key] - other_analyzer.model1_avg_translation_errs[key]
+    #     delta_num_model0[key] = mm_analyzer.model0_num_frames[key]- other_analyzer.model0_num_frames[key]
+    #     delta_num_model1[key] = mm_analyzer.model1_num_frames[key] - other_analyzer.model1_num_frames[key]
+
+    # print(f"Test Time: {MULTI_MODEL_TEST_METADATA_MAPPINGS[dataset_name]}")
+    # print("All Calculations are Rotated Results minus Original Results")
+    # import pprint
+    # print("Results of Model Trained on Night Dataset (9:30 PM)")
+    # print("Delta Translational Error:")
+    # pprint.pp(delta_trans_model0)
+    # print("Delta Number of Frames:")
+    # pprint.pp(delta_num_model0)
+    # print("Results of Model Trained on Day Dataset (12:00 PM)")
+    # print("Delta Translational Error:")
+    # pprint.pp(delta_trans_model1)
+    # print("Delta Number of Frames:")
+    # pprint.pp(delta_num_model1)
+    # print("\n\n\n")
 
+    fig = plt.figure()
     plt.rcParams.update({"font.size": 8})
     ax = fig.add_subplot(2, 2, 1)
     independent_trans_errs = mm_analyzer.independent_avg_translation_errs
@@ -329,7 +371,7 @@ def analyze_multi_model_datasets(dataset_name, visualize: bool, save: bool):
 
     if save:
         plt.savefig(
-            FIGURE_DIR / f"multimodel/{dataset_name.split('_')[1]}/trans_err_bar"
+            FIGURE_DIR / f"better_enhancement_multimodel/{dataset_name.split('_')[1]}/trans_err_bar"
         )
 
     if visualize:
@@ -399,7 +441,7 @@ def analyze_multi_model_datasets(dataset_name, visualize: bool, save: bool):
     )
 
     if save:
-        plt.savefig(FIGURE_DIR / f"multimodel/{dataset_name.split('_')[1]}/frame_bar")
+        plt.savefig(FIGURE_DIR / f"better_enhancement_multimodel/{dataset_name.split('_')[1]}/frame_bar")
 
     if visualize:
         plt.show()
@@ -478,7 +520,7 @@ def analyze_multi_model_datasets(dataset_name, visualize: bool, save: bool):
             args.s
             and args.mm
             and not (
-                dir := FIGURE_DIR / f"multimodel/{dataset_name.split('_')[1]}"
+                dir := FIGURE_DIR / f"better_enhancement_multimodel/{dataset_name.split('_')[1]}"
             ).exists()
         ):
             os.mkdir(dir)