increase training crop + new edges for Karusell

increase training crop dtom 769 t o1281 for all models + 7 edges for Karusell dataset_v2_88

Grand_Prix/Inference/predict.ipynb

@@ -4,7 +4,11 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "120b4212",
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": [
     "!python -m openpifpaf.predict test\\images\\test.png \\\n",
@@ -18,7 +22,11 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "984d60d5",
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": [
     "# !python -m openpifpaf.video --source test\\videos\\test.mp4 \\\n",

Grand_Prix/Supervisely/GrandPrix_create_3d_15.ipynb

@@ -2,9 +2,13 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "9b13894c",
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": [
     "import json\n",
@@ -26,9 +30,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 178,
+   "execution_count": 2,
    "id": "39604368",
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": [
     "img = cv2.imread('Grand_Prix_GPS-double.png')\n",
@@ -41,7 +49,7 @@
     "df['z'] = 4.2*np.float32([0, 0, 0, 0, 3, 6.33, 7.33, 3.33, 2.33, 2.33, 2.33, 2.5, 2.5, 1.2,1.5])\n",
     "df[['x', 'y']] /= 8.4\n",
     "df[['x', 'y']] = df.values[:, :2]@roration(-135) # поворот x и y в плоскости земли\n",
-    "# df.to_csv('GrandPrix_15kps.csv')\n",
+    "df.to_csv('GrandPrix_15kps.csv')\n",
     "\n",
     "# rvec, tvec, camMatrx, dist = fit(img.shape[:2], df_raw, df)\n",
     "# imgpts = cv.projectPoints(5*arrow, rvec, tvec, camMatrx, dist)[0][:, 0].astype(int)\n",
@@ -54,7 +62,11 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "82d1f0f1",
-   "metadata": {},
+   "metadata": {
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [],
    "source": []
   }