Upload sensAI-Generic-Object-Detection with upload_repo.py

README.md

@@ -31,13 +31,12 @@ an uploaded video, or a live webcam feed. Pick exactly one of three models:
 
 | Model | Description |
 | --- | --- |
-| **GMOD-80** | Generic 80-class object detector |
-| **AMOD-8**  | 8-class automotive object detector — person, bicycle, car, motorcycle, truck, bus, traffic light, stop sign |
-| **OMOD-8**    | 8-class office-objects detector — bottle, cup, potted plant, laptop, mouse, keyboard, cell phone, book |
+| **GMOD Base Model** | Generic 80-class object detector |
+| **Automotive Object Detector**  | 8-class automotive object detector — person, bicycle, car, motorcycle, truck, bus, traffic light, stop sign |
+| **Office Object Detector**    | 8-class office-objects detector — bottle, cup, potted plant, laptop, mouse, keyboard, cell phone, book |
 
 Each model is a self-contained `.tflite` loaded through the EVE SDK's custom
-object-detection model path. GMOD-80 uses the SDK's bundled weights; AMOD-8 and
-OMOD-8 load from `models/`. Selecting a model in either tab loads it on the worker.
+object-detection model path. GMOD Base Model uses the SDK's bundled weights. Selecting a model in either tab loads it on the worker.
 
 To preview the demo, use the tabs:
 

app.py

@@ -40,8 +40,8 @@ def _build_feature_radio(hint: str = "") -> gr.Radio:
         choices=MOD_MODELS,
         value=DEFAULT_MOD_MODEL,
         label=label,
-        info="Pick one object detector: GMOD-80 (generic 80-class), Automotive finetune (8-class)"
-        ", or Office finetune (8-class).",
+        info="Pick one object detector: GMOD Base Model (generic 80-class), Automotive Object Detector (8-class)"
+        ", or Office Object Detector (8-class).",
         interactive=True,
     )
 
@@ -155,26 +155,28 @@ if __name__ == "__main__":
         gr.Markdown(
             "Run object detection on videos or a live camera feed using "
             "one of three EVE SDK models:\n\n"
-            "- **GMOD-80** — 80-class generic multi-object detector.\n\n"
-            "   - Classes: person, bicycle, car, motorcycle, airplane, bus, train, truck, boat, "
-            "traffic light, fire hydrant, stop sign, parking meter, bench, bird, cat, dog, horse, "
-            "sheep, cow, elephant, bear, zebra, giraffe, backpack, umbrella, handbag, tie, suitcase, "
-            "frisbee, skis, snowboard, sports ball, kite, baseball bat, baseball glove, skateboard, "
-            "surfboard, tennis racket, bottle, wine glass, cup, fork, knife, spoon, bowl, banana, "
-            "apple, sandwich, orange, broccoli, carrot, hot dog, pizza, donut, cake, chair, couch, "
-            "potted plant, bed, dining table, toilet, tv, laptop, mouse, remote, keyboard, cell phone, "
-            "microwave, oven, toaster, sink, refrigerator, book, clock, vase, scissors, teddy bear, "
-            "hair drier and toothbrush.\n\n"
-            "- **Automotive finetune** — 8-class automotive object detector finetuned from GMOD-80.\n\n"
+            "- **GMOD Base Model** — 80-class generic multi-object detector.\n\n"
+            "   - Classes, grouped by category:\n\n"
+            "     - **People and animals:** person, bird, cat, dog, horse, sheep, cow, elephant, bear, zebra and giraffe.\n"
+            "     - **Vehicles:** bicycle, car, motorcycle, airplane, bus, train, truck and boat.\n"
+            "     - **Outdoor:** traffic light, fire hydrant, stop sign, parking meter and bench.\n"
+            "     - **Accessories:** backpack, umbrella, handbag, tie and suitcase.\n"
+            "     - **Sports:** frisbee, skis, snowboard, sports ball, kite, baseball bat, baseball glove, skateboard, surfboard and tennis racket.\n"
+            "     - **Kitchen:** bottle, wine glass, cup, fork, knife, spoon and bowl.\n"
+            "     - **Food:** banana, apple, sandwich, orange, broccoli, carrot, hot dog, pizza, donut and cake.\n"
+            "     - **Furniture:** chair, couch, potted plant, bed, dining table and toilet.\n"
+            "     - **Electronics:** tv, laptop, mouse, remote, keyboard and cell phone.\n"
+            "     - **Appliances:** microwave, oven, toaster, sink and refrigerator.\n"
+            "     - **Indoor:** book, clock, vase, scissors, teddy bear, hair drier and toothbrush.\n\n"
+            "- **Automotive Object Detector** — 8-class automotive object detector finetuned from GMOD Base Model.\n\n"
             "   - Classes: person, bicycle, car, motorcycle, bus, truck, traffic light and stop sign.\n"
-            "- **Office finetune** — 8-class office object detector finetuned from GMOD-80.\n\n"
+            "- **Office Object Detector** — 8-class office object detector finetuned from GMOD Base Model.\n\n"
             "   - Classes: bottle, cup, potted plant, laptop, mouse, keyboard, cell phone and book.\n\n"
             "Only one model is active at a time. Pick the model with the radio button below."
         )
         gr.Markdown(
-            "A guide on how to finetune the GMOD-80 model with your own data will be available soon, along with the release 7.3 of the EVE SDK.\n\n"
-            "For any questions or support, please reach out to us at evehelp@latticesemi.com.\n\n"
-            "> Note: For demo purposes, execution of the AI pipeline and image draw operations are all performed on a Hugging Face CPU server. Performance may vary based on the number of concurrent users."
+            "A guide on how to finetune the GMOD Base Model with your own data will be available soon, along with the release 7.3 of the EVE SDK.\n\n"
+            "For any questions or support, please reach out to us at evehelp@latticesemi.com."
         )
 
         # Required by EveAppHandlers signatures (Face ID gallery state). Empty
@@ -203,6 +205,13 @@ if __name__ == "__main__":
 
             build_eula_tab()
 
+        gr.Markdown(
+            "<p style='font-size:1.0em;text-align:center'>"
+            "<strong>Note:</strong> For demo purposes, execution of the AI pipeline and image draw "
+            "operations are all performed on a Hugging Face CPU server. Performance may vary based on "
+            "the number of concurrent users.</p>"
+        )
+
         # --- Examples wire-up: clicking a sample loads it into the matching input ---
         video_example_dataset.click(
             fn=lambda sample: sample[0],

mod_models.py

@@ -4,9 +4,10 @@ This is the single place that maps each selectable model name to the
 ``ModelConfig`` the EVE worker loads. Adding a model, or pointing an existing
 one at new weights, is a one-line change here — nothing else needs to move.
 
-- **GMOD-80** uses the EVE SDK's bundled default model, so it carries no path
-  and no class table.
-- **Automotive** and **Office** load their ``.tflite`` from ``MOD_MODELS_DIR``
+- **GMOD Base Model** uses the EVE SDK's bundled default model, so it carries
+  no path and no class table.
+- **Automotive Object Detector** and **Office Object Detector** load their
+  ``.tflite`` from ``MOD_MODELS_DIR``
   (the gated weights fetched at build time, see ``install_eve.py``; falls back to
   the demo-relative ``models/`` locally) and ship their own class labels (in
   output-index order).
@@ -46,16 +47,16 @@ OFFICE_CLASS_NAMES: tuple[str, ...] = (
 )
 
 MOD_MODEL_REGISTRY: dict[str, ModelConfig] = {
-    "GMOD-80": ModelConfig(name="GMOD-80", nms_threshold=0.2),
-    "Automotive": ModelConfig(
-        name="Automotive",
+    "GMOD Base Model": ModelConfig(name="GMOD Base Model", nms_threshold=0.2),
+    "Automotive Object Detector": ModelConfig(
+        name="Automotive Object Detector",
         model_path=str(_MODELS_DIR / "automotive-640x640.tflite"),
         class_names=AUTOMOTIVE_CLASS_NAMES,
         nms_threshold=0.4,
         iou_threshold=0.4
     ),
-    "Office": ModelConfig(
-        name="Office",
+    "Office Object Detector": ModelConfig(
+        name="Office Object Detector",
         model_path=str(_MODELS_DIR / "office-640x640.tflite"),
         class_names=OFFICE_CLASS_NAMES,
         nms_threshold=0.4,
@@ -65,4 +66,4 @@ MOD_MODEL_REGISTRY: dict[str, ModelConfig] = {
 
 # UI order of the selection radio; first entry is the default.
 MOD_MODELS: list[str] = list(MOD_MODEL_REGISTRY)
-DEFAULT_MOD_MODEL: str = "GMOD-80"
+DEFAULT_MOD_MODEL: str = "GMOD Base Model"

shared/eve_messages.py

@@ -26,7 +26,7 @@ class ModelConfig:
 
     Carries everything ``eve_wrapper.enable_object_detection`` needs to
     configure one MOD model. ``model_path`` of ``None`` / ``""`` selects the
-    EVE SDK's bundled default model (GMOD-80); a path loads that ``.tflite``
+    EVE SDK's bundled default model (GMOD Base Model); a path loads that ``.tflite``
     and applies ``class_names``. ``None`` thresholds fall back to the SDK
     defaults. Picklable so it can ride inside ``FeatureFlags`` to a worker.
 

shared/eve_wrapper.py

@@ -257,7 +257,7 @@ class EveWrapper:
         it, matching the SDK's disabled-by-default state). Otherwise:
 
         - ``config.model_path`` empty / ``None`` selects the SDK's bundled
-          default model (GMOD-80) with its default class names.
+          default model (GMOD Base Model) with its default class names.
         - a populated ``config.model_path`` loads that ``.tflite`` and, if
           given, replaces the class table with ``config.class_names``.