add models

app.py

@@ -8,67 +8,12 @@ from huggingface_hub import hf_hub_download
 backend = get_backend('ultralytics')
 
 # Make sure the models paths are defined wrt their tasks, it helps map task in backend
-def use_models_hf():
-    model_repos = {
-        "Classification": {
-            "repo_id": "Synaptics/sr100_person_classification_448x640",
-            "filename": "person_classification_flash(448x640).tflite",
-            "local_dir": "model/classify"
-        },
-        "Detection": {
-            "repo_id": "Synaptics/sr100_person_detection_480x640",
-            "filename": "person_detection_flash(480x640).tflite",
-            "local_dir": "model/detect"
-        },
-        "Pose": {
-            "repo_id": "Synaptics/sr100_person_pose_detection_480x640",
-            "filename": "person_pose_detection_flash(480x640).tflite",
-            "local_dir": "model/pose"
-        },
-        "Segmentation": {
-            "repo_id": "Synaptics/sr100_person_segmentation_480x640",
-            "filename": "person_segmentation_flash(480x640).tflite",
-            "local_dir": "model/segment"
-        }
-    }
-    
-    downloaded_models = {}
-    
-    os.makedirs("model", exist_ok=True)
-    
-    for model_type, model_info in model_repos.items():
-        os.makedirs(model_info["local_dir"], exist_ok=True)
-    
-    for model_type, model_info in model_repos.items():
-        target_path = os.path.join(model_info["local_dir"], model_info["filename"])
-        
-        if os.path.exists(target_path):
-            print(f"Model already exists at {target_path}")
-            downloaded_models[model_type] = target_path
-            continue
-        
-        try:
-            print(f"Downloading {model_type} model from Hugging Face...")
-            model_path = hf_hub_download(
-                repo_id=model_info["repo_id"],
-                filename=model_info["filename"],
-                local_dir=model_info["local_dir"],  
-                local_dir_use_symlinks=False  
-            )
-            
-            downloaded_models[model_type] = model_path
-            print(f"Successfully downloaded {model_type} model to {model_path}")
-        except Exception as e:
-            print(f"Error downloading {model_type} model: {e}")
-            # Fallback to local path if download fails
-            downloaded_models[model_type] = target_path
-            print(f"Falling back to local path: {target_path}")
-    
-    return downloaded_models
-
-# Get model paths from Hugging Face
-model_paths = use_models_hf()
-
+model_paths = {
+    "Classification": "model/classify/person_classification_flash(448x640).tflite",
+    "Detection": "model/detect/person_detection_flash(480x640).tflite",
+    "Pose": "model/pose/person_pose_detection_flash(480x640).tflite",
+    "Segmentation": "model/segment/person_segmentation_flash(480x640).tflite"
+}
 
 selected_model_name = "Classification"
 backend.patch(model_paths[selected_model_name])

model/classify/person_classification_flash(448x640).tflite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cef272090b9d1f098b5b1e886c02f73aef8ba3a17746000af803e941d24a46a5
+size 1526416

model/detect/person_detection_flash(480x640).tflite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d498a99939b4f6654dd5c6286a5fcf281fc11dfb84f62b412e2782796fd4fa4d
+size 1262040

model/pose/person_pose_detection_flash(480x640).tflite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:65290b73151b7b7ffbb0a182abc863a3fc656e77ff67c57be25013fc1b929e50
+size 1530504

model/segment/person_segmentation_flash(480x640).tflite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:434116fec61c9214447aa391141dd8c0c329f27e19bd525ad51cc00544c748e7
+size 1524648