Replace HRNet with SEResNet model in the notebook

examples/interpretation/notebooks/Dutch_F3_patch_model_training_and_evaluation.ipynb

@@ -59,7 +59,7 @@
    "source": [
     "# load an existing experiment configuration file\n",
     "CONFIG_FILE = (\n",
-    "    \"../../../experiments/interpretation/dutchf3_patch/local/configs/hrnet.yaml\"\n",
+    "    \"../../../experiments/interpretation/dutchf3_patch/local/configs/seresnet_unet.yaml\"\n",
     ")\n",
     "# number of images to score\n",
     "N_EVALUATE = 20\n",
@@ -239,7 +239,7 @@
     "max_snapshots = config.TRAIN.SNAPSHOTS\n",
     "papermill = False\n",
     "dataset_root = config.DATASET.ROOT\n",
-    "model_pretrained = config.MODEL.PRETRAINED"
+    "model_pretrained = config.MODEL.PRETRAINED if \"PRETRAINED\" in config.MODEL.keys() else None"
    ]
   },
   {
@@ -859,9 +859,18 @@
    "outputs": [],
    "source": [
     "# use the model which we just fine-tuned\n",
-    "opts = [\"TEST.MODEL_PATH\", path.join(output_dir, f\"model_f3_nb_seg_hrnet_{train_len}.pth\")]\n",
+    "if \"hrnet\" in config.MODEL.NAME:\n",
+    "    model_snapshot_name = f\"model_f3_nb_seg_hrnet_{train_len}.pth\"\n",
+    "elif \"resnet\" in config.MODEL.NAME:    \n",
+    "    model_snapshot_name = f\"model_f3_nb_resnet_unet_{train_len}.pth\"\n",
+    "else:\n",
+    "    raise NotImplementedError(\"We don't support testing this model in this notebook yet\")\n",
+    "    \n",
+    "opts = [\"TEST.MODEL_PATH\", path.join(output_dir, model_snapshot_name)]\n",
+    "\n",
     "# uncomment the line below to use the pre-trained model instead\n",
     "# opts = [\"TEST.MODEL_PATH\", config.MODEL.PRETRAINED]\n",
+    "\n",
     "config.merge_from_list(opts)"
    ]
   },

examples/interpretation/notebooks/utilities.py

@@ -328,23 +328,23 @@ def download_pretrained_model(config):
         raise NameError(
             "Unknown dataset name. Only dutch f3 and penobscot are currently supported."
         )
-
+    
     if "hrnet" in config.MODEL.NAME:
         model = "hrnet"
     elif "deconvnet" in config.MODEL.NAME:
         model = "deconvnet"
-    elif "unet" in config.MODEL.NAME:
-        model = "unet"
+    elif "resnet" in config.MODEL.NAME:
+        model = "seresnetunet"    
     else:
         raise NameError(
-            "Unknown model name. Only hrnet, deconvnet, and unet are currently supported."
+            "Unknown model name. Only hrnet, deconvnet, and seresnet_unet are currently supported."
         )
 
     # check if the user already supplied a URL, otherwise figure out the URL
-    if validators.url(config.MODEL.PRETRAINED):
+    if "PRETRAINED" in config.MODEL.keys() and validators.url(config.MODEL.PRETRAINED):
         url = config.MODEL.PRETRAINED
         print(f"Will use user-supplied URL of '{url}'")
-    elif os.path.isfile(config.MODEL.PRETRAINED):
+    elif "PRETRAINED" in config.MODEL.keys() and os.path.isfile(config.MODEL.PRETRAINED):
         url = None
         print(f"Will use user-supplied file on local disk of '{config.MODEL.PRETRAINED}'")
     else:
@@ -371,19 +371,20 @@ def download_pretrained_model(config):
                 and config.TRAIN.DEPTH == "none"
             ):
                 url = "http://deepseismicsharedstore.blob.core.windows.net/master-public-models/dutchf3_deconvnetskip_patch_no_depth.pth"
-
             elif (
                 model == "deconvnet"
                 and "skip" not in config.MODEL.NAME
                 and config.TRAIN.DEPTH == "none"
             ):
-                url = "http://deepseismicsharedstore.blob.core.windows.net/master-public-models/dutchf3_deconvnet_patch_no_depth.pth"
-            elif model == "unet" and config.TRAIN.DEPTH == "section":
-                url = "http://deepseismicsharedstore.blob.core.windows.net/master-public-models/dutchf3_seresnetunet_patch_section_depth.pth"
+                url = "http://deepseismicsharedstore.blob.core.windows.net/master-public-models/dutchf3_deconvnet_patch_no_depth.pth"            
+            elif model == "seresnetunet" and config.TRAIN.DEPTH == "section":
+                url = "https://deepseismicsharedstore.blob.core.windows.net/master-public-models/dutchf3_seresnetunet_patch_section_depth.pth"
             else:
                 raise NotImplementedError(
                     "We don't store a pretrained model for Dutch F3 for this model combination yet."
                 )
+
+
         else:
             raise NotImplementedError(
                 "We don't store a pretrained model for this dataset/model combination yet."
@@ -424,6 +425,11 @@ def download_pretrained_model(config):
     # Update config MODEL.PRETRAINED
     # TODO: Only HRNet uses a pretrained model currently.
     # issue https://github.com/microsoft/seismic-deeplearning/issues/267
+
+    # now that we have a pre-trained model, we can set it
+    if "PRETRAINED" not in config.MODEL.keys():
+        config.MODEL["PRETRAINED"] = "dummy"
+
     opts = [
         "MODEL.PRETRAINED",
         pretrained_model_path,
@@ -432,6 +438,7 @@ def download_pretrained_model(config):
         "TEST.MODEL_PATH",
         pretrained_model_path,
     ]
+
     config.merge_from_list(opts)
 
     return config

experiments/interpretation/dutchf3_patch/local/configs/seresnet_unet.yaml

@@ -9,11 +9,12 @@ WORKERS: 4
 PRINT_FREQ: 10
 LOG_CONFIG: logging.conf
 SEED: 2019
+OPENCV_BORDER_CONSTANT: 0
 
 
 DATASET:
   NUM_CLASSES: 6
-  ROOT: /home/username/data/dutch/data
+  ROOT: "/home/username/data/dutch/data"
   CLASS_WEIGHTS: [0.7151, 0.8811, 0.5156, 0.9346, 0.9683, 0.9852]
   MIN: -1
   MAX: 1