move examples to docs

weecology · Oct 25, 2024 · 12ce8bb · 12ce8bb
1 parent 2412f93
commit 12ce8bb
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diff --git a/examples/DeepForest.py → DeepForest.py b/examples/DeepForest.py → DeepForest.py
@@ -7,7 +7,7 @@
 
 from milliontrees import get_dataset
 from milliontrees.common.data_loaders import get_train_loader
-from deepforest import main
+from deepforest.main import deepforest
 from pytorch_lightning.loggers import CometLogger
 
 def parse_args():
@@ -37,7 +37,8 @@ def main():
     train_dataset = dataset.get_subset("train")
     train_loader = get_train_loader("standard", train_dataset, batch_size=2)
 
-    m = main.deepforest(config_args=kwargs)
+    m = deepforest(config_args=kwargs)
+    m.config["train"]["csv_file"] ="<dummy file, existing dataloader>"
 
     # Load the pre-trained tree model
     m.load_model("Weecology/DeepForest-tree")

diff --git a/deepforest_config.yml b/deepforest_config.yml
@@ -0,0 +1,60 @@
+# Config file for DeepForest pytorch module
+
+# Cpu workers for data loaders
+# Dataloaders
+workers: 0
+devices: auto
+accelerator: auto
+batch_size: 2
+
+# Model Architecture
+architecture: 'retinanet'
+num_classes: 1
+nms_thresh: 0.05
+
+# Architecture specific params
+retinanet:
+    # Non-max supression of overlapping predictions
+    score_thresh: 0.1
+
+train:
+    csv_file:
+    root_dir:
+
+    # Optimizer initial learning rate
+    lr: 0.00001
+    scheduler:
+        type: 
+        params:
+            # Common parameters
+            T_max: 10
+            eta_min: 0.00001
+            lr_lambda: "lambda epoch: 0.95 ** epoch"  # For lambdaLR and multiplicativeLR
+            step_size: 30  # For stepLR
+            gamma: 0.1  # For stepLR, multistepLR, and exponentialLR
+            milestones: [50, 100]  # For multistepLR
+
+            # ReduceLROnPlateau parameters (used if type is not explicitly mentioned)
+            mode: "min"
+            factor: 0.1
+            patience: 10
+            threshold: 0.0001
+            threshold_mode: "rel"
+            cooldown: 0
+            min_lr: 0
+            eps: 1e-08
+
+    # Print loss every n epochs
+    epochs: 1
+    # Useful debugging flag in pytorch lightning, set to True to get a single batch of training to test settings.
+    fast_dev_run: False
+    # pin images to GPU memory for fast training. This depends on GPU size and number of images.
+    preload_images: False
+
+validation:
+    # callback args
+    csv_file: 
+    root_dir:
+    # Intersection over union evaluation
+    iou_threshold: 0.4
+    val_accuracy_interval: 20
diff --git a/examples/Datasets.ipynb → docs/examples/Datasets.ipynb b/examples/Datasets.ipynb → docs/examples/Datasets.ipynb
diff --git a/examples/baseline_boxes.ipynb → docs/examples/baseline_boxes.ipynb b/examples/baseline_boxes.ipynb → docs/examples/baseline_boxes.ipynb
diff --git a/docs/index.rst b/docs/index.rst
@@ -45,4 +45,5 @@ Forests underlie many ecosystem services, agricultural systems and urban plannin
    contributing
    developer
    source/modules.rst
+   examples/Datasets.ipynb
 
diff --git a/examples/inspect.ipynb b/examples/inspect.ipynb
diff --git a/submit_DeepForest.sh b/submit_DeepForest.sh
@@ -21,4 +21,4 @@ export COMET_WORKSPACE=bw4sz
 #Add to path
 export PYTHONPATH=$PYTHONPATH:/home/b.weinstein/MillionTrees
 
-python examples/DeepForest.py
+python DeepForest.py