update UI + latest yolov5 sources

requirements.txt

@@ -1,5 +1,5 @@
 # pip install -r requirements.txt
-supervisely==6.1.52
+supervisely==6.1.74
 
 # base ----------------------------------------
 #matplotlib>=3.2.2
@@ -8,21 +8,17 @@ supervisely==6.1.52
 #Pillow
 PyYAML>=5.3.1
 #scipy>=1.4.1
-torch>=1.7.0
-torchvision>=0.8.1
+#torch>=1.7.0
+#torchvision>=0.8.1
 tqdm>=4.41.0
 
 # logging -------------------------------------
 tensorboard>=2.4.1
 # wandb
 
-# logging -------------------------------------
-tensorboard>=2.4.1
-# wandb
-
 # plotting ------------------------------------
 seaborn==0.11.1
-pandas
+#pandas
 
 # export --------------------------------------
 # coremltools>=4.1

supervisely/train/config.json

@@ -19,5 +19,5 @@
     "context_root": "Neural Networks",
     "context_category": "YOLO v5"
   },
-  "instance_version": "6.3.2"
+  "instance_version": "6.4.14"
 }

supervisely/train/debug.env

@@ -2,14 +2,13 @@ PYTHONUNBUFFERED=1
 
 DEBUG_APP_DIR="/app_debug_data"
 DEBUG_CACHE_DIR="/app_cache"
+LOG_LEVEL="debug"
 
-TASK_ID=2391
+TASK_ID=4326
 
-context.teamId=7
-context.workspaceId=263
-#modal.state.slyProjectId=1843  # coco-128
-modal.state.slyProjectId=1805  # lemons-annotated
-#modal.state.slyFile="put your value here"
+context.teamId=229
+context.workspaceId=287
+modal.state.slyProjectId=2128  # lemons-annotated
 
 SERVER_ADDRESS="put your value here"
 API_TOKEN="put your value here"

supervisely/train/src/sly_metrics.py

@@ -1,5 +1,5 @@
 import supervisely_lib as sly
-import sly_train_globals as globals
+import supervisely.train.src.sly_train_globals as globals
 
 
 def init_chart(title, names, xs, ys, smoothing=None):
@@ -24,19 +24,19 @@ def init_chart(title, names, xs, ys, smoothing=None):
 def init(data, state):
     demo_x = [[], []] #[[1, 2, 3, 4], [2, 4, 6, 8]]
     demo_y = [[], []] #[[10, 15, 13, 17], [16, 5, 11, 9]]
-    data["mBox"] = init_chart("Box Loss",
-                              names=["train", "val"],
-                              xs=demo_x,
-                              ys=demo_y,
-                              smoothing=0.6)
+    data["mGIoU"] = init_chart("GIoU",
+                               names=["train", "val"],
+                               xs=demo_x,
+                               ys=demo_y,
+                               smoothing=0.6)
 
-    data["mObjectness"] = init_chart("Obj Loss",
+    data["mObjectness"] = init_chart("Objectness",
                                      names=["train", "val"],
                                      xs=demo_x,
                                      ys=demo_y,
                                      smoothing=0.6)
 
-    data["mClassification"] = init_chart("Cls Loss",
+    data["mClassification"] = init_chart("Classification",
                                          names=["train", "val"],
                                          xs=demo_x,
                                          ys=demo_y,
@@ -54,23 +54,24 @@ def init(data, state):
     state["smoothing"] = 0.6
 
 
-def send_metrics(epoch, epochs, metrics):
+def send_metrics(epoch, epochs, metrics, log_period=1):
     sly.logger.debug(f"Metrics: epoch {epoch} / {epochs}", extra={"metrics": metrics})
 
-    fields = [
-        {"field": "data.mBox.series[0].data", "payload": [[epoch, metrics["train/box_loss"]]], "append": True},
-        {"field": "data.mBox.series[1].data", "payload": [[epoch, metrics["val/box_loss"]]], "append": True},
+    if epoch % log_period == 0 or epoch == epochs:
+        fields = [
+            {"field": "data.mGIoU.series[0].data", "payload": [[epoch, metrics["train/box_loss"]]], "append": True},
+            {"field": "data.mGIoU.series[1].data", "payload": [[epoch, metrics["val/box_loss"]]], "append": True},
 
-        {"field": "data.mObjectness.series[0].data", "payload": [[epoch, metrics["train/obj_loss"]]], "append": True},
-        {"field": "data.mObjectness.series[1].data", "payload": [[epoch, metrics["val/obj_loss"]]], "append": True},
+            {"field": "data.mObjectness.series[0].data", "payload": [[epoch, metrics["train/obj_loss"]]], "append": True},
+            {"field": "data.mObjectness.series[1].data", "payload": [[epoch, metrics["val/obj_loss"]]], "append": True},
 
-        {"field": "data.mClassification.series[0].data", "payload": [[epoch, metrics["train/cls_loss"]]], "append": True},
-        {"field": "data.mClassification.series[1].data", "payload": [[epoch, metrics["val/cls_loss"]]], "append": True},
+            {"field": "data.mClassification.series[0].data", "payload": [[epoch, metrics["train/cls_loss"]]], "append": True},
+            {"field": "data.mClassification.series[1].data", "payload": [[epoch, metrics["val/cls_loss"]]], "append": True},
 
-        {"field": "data.mPR.series[0].data", "payload": [[epoch, metrics["metrics/precision"]]], "append": True},
-        {"field": "data.mPR.series[1].data", "payload": [[epoch, metrics["metrics/recall"]]], "append": True},
+            {"field": "data.mPR.series[0].data", "payload": [[epoch, metrics["metrics/precision"]]], "append": True},
+            {"field": "data.mPR.series[1].data", "payload": [[epoch, metrics["metrics/recall"]]], "append": True},
 
-        {"field": "data.mMAP.series[0].data", "payload": [[epoch, metrics["metrics/mAP_0.5"]]], "append": True},
-        {"field": "data.mMAP.series[1].data", "payload": [[epoch, metrics["metrics/mAP_0.5:0.95"]]], "append": True},
-    ]
-    globals.api.app.set_fields(globals.task_id, fields)
+            {"field": "data.mMAP.series[0].data", "payload": [[epoch, metrics["metrics/mAP_0.5"]]], "append": True},
+            {"field": "data.mMAP.series[1].data", "payload": [[epoch, metrics["metrics/mAP_0.5:0.95"]]], "append": True},
+        ]
+        globals.api.app.set_fields(globals.task_id, fields)