demo

.gitignore

@@ -1,3 +1,6 @@
+models/.locks
+models/models*
+
 Demo/flagged/
 
 

app.py

@@ -2,6 +2,12 @@ import gradio as gr
 import torch
 from src.predict import predict_from_video
 from src.islr.islr_model import DummyISLRModel
+from huggingface_hub import hf_hub_download
+import torch
+import os
+
+# Crea carpeta si no existe
+os.makedirs("models", exist_ok=True)
 
 
 #device = 'cpu'
@@ -35,6 +41,14 @@ dataset_examples = {
 def load_model_and_examples(dataset):
     model_path  = dataset_models.get(dataset)['path']
     num_classes = dataset_models.get(dataset)['num_classes']
+    print("Downloading..")
+    model_path = hf_hub_download(repo_id="CristianLazoQuispe/SignERT", filename=model_path,
+                                     cache_dir="models"  # guarda el archivo y cachea en esa carpeta                    
+                                )
+    print("Downloaded!")
+    #model.load_state_dict(torch.load(model_path, map_location="cpu"))
+
+
     model = DummyISLRModel(num_classes=num_classes)
     model.load_state_dict(torch.load(model_path, map_location=device))
     model.eval()