add url

model/models.py

@@ -0,0 +1,60 @@
+import urllib.request
+import tarfile
+from tqdm import tqdm
+import os
+import yaml
+from ruamel.yaml import YAML
+
+def read_plainconfig(configname):
+    if not os.path.exists(configname):
+        raise FileNotFoundError(
+            f"Config {configname} is not found. Please make sure that the file exists."
+        )
+    with open(configname) as file:
+        return YAML().load(file)
+
+def DownloadModel(modelname, target_dir):
+    """
+    Downloads a DeepLabCut Model Zoo Project
+    """
+    
+    def show_progress(count, block_size, total_size):
+        pbar.update(block_size)
+
+    def tarfilenamecutting(tarf):
+        """' auxfun to extract folder path
+        ie. /xyz-trainsetxyshufflez/
+        """
+        for memberid, member in enumerate(tarf.getmembers()):
+            if memberid == 0:
+                parent = str(member.path)
+                l = len(parent) + 1
+            if member.path.startswith(parent):
+                member.path = member.path[l:]
+                yield member
+
+    neturls = read_plainconfig("/home/sabrina/MegaDetector_DeepLabCut/model/pretrained_model_urls.yaml") #FIXME
+    
+    if modelname in neturls.keys():
+        url = neturls[modelname]
+        print(url)
+        response = urllib.request.urlopen(url)
+        print(
+            "Downloading the model from the DeepLabCut server @Harvard -> Go Crimson!!! {}....".format(
+                url
+            )
+        )
+        total_size = int(response.getheader("Content-Length"))
+        pbar = tqdm(unit="B", total=total_size, position=0)
+        filename, _ = urllib.request.urlretrieve(url, reporthook=show_progress)
+        with tarfile.open(filename, mode="r:gz") as tar:
+            tar.extractall(target_dir, members=tarfilenamecutting(tar))
+    else:
+        models = [
+            fn
+            for fn in neturls.keys()
+            if "resnet_" not in fn and "mobilenet_" not in fn
+        ]
+        print("Model does not exist: ", modelname)
+        print("Pick one of the following: ", models)
+    return target_dir

model/pretrained_model_urls.yaml

@@ -0,0 +1,9 @@
+#Model Zoo from where the Charles flow(s)
+full_human: http://deeplabcut.rowland.harvard.edu/models/DLC_human_fullbody_resnet_101.tar.gz
+full_dog: http://deeplabcut.rowland.harvard.edu/models/DLC_Dog_resnet_50_iteration-0_shuffle-0.tar.gz
+full_cat: http://deeplabcut.rowland.harvard.edu/models/DLC_Cat_resnet_50_iteration-0_shuffle-0.tar.gz
+primate_face: http://deeplabcut.rowland.harvard.edu/models/DLC_primate_face_resnet_50_iteration-1_shuffle-1.tar.gz
+mouse_pupil_vclose: http://deeplabcut.rowland.harvard.edu/models/DLC_mouse_pupil_vclose_resnet_50_iteration-0_shuffle-1.tar.gz
+horse_sideview: http://deeplabcut.rowland.harvard.edu/models/DLC_Horses_resnet_50_iteration-1_shuffle-1.tar.gz
+full_macaque: http://deeplabcut.rowland.harvard.edu/models/DLC_macaque_full_resnet50.tar.gz
+full_cheetah: http://deeplabcut.rowland.harvard.edu/models/DLC_full_cheetah_resnet_152.tar.