Migrated to nix for dependency managment

dodgeballtracker/__init__.py

@@ -1,24 +0,0 @@
-from pathlib import Path
-
-from dodgeballtracker.logic import (DetectedObjectBox,
-                                    DodgeballTracker,
-                                    get_court_perspective_transform)
-import numpy as np
-
-
-here = Path(__file__).parent
-input_dir = here / '..' / 'data'
-output_dir = here / '..' / 'outputs'
-
-if __name__ == "__main__":
-    detected_box_objects = [
-        DetectedObjectBox.from_viridis(threshold) for threshold in np.arange(0.5, 1, 0.05)
-    ]
-    input_video = input_dir / "micro.mp4"
-    output_video = output_dir / "output-lmbn_n_cuhk03_d.mp4"
-
-    transformation_matrix = get_court_perspective_transform()
-
-    dodgeball_tracker = DodgeballTracker(input_video, output_video, detected_box_objects, transformation_matrix)
-
-    dodgeball_tracker.main()

dodgeballtracker/__main__.py

@@ -0,0 +1,28 @@
+from pathlib import Path
+
+from dodgeballtracker.logic import (DetectedObjectBox,
+                                    DodgeballTracker,
+                                    get_court_perspective_transform)
+import numpy as np
+import logging
+
+
+here = Path(__file__).parent
+input_dir = here / '..' / 'data'
+output_dir = here / '..' / 'outputs'
+
+if __name__ == "__main__":
+    logging.basicConfig(filename='tracker.log', level=logging.DEBUG)
+
+    detected_box_objects = [
+        DetectedObjectBox.from_viridis(threshold) for threshold in np.arange(0.5, 1, 0.05)
+    ]
+
+    input_video = input_dir / "small.mp4"
+    output_video = output_dir / "foo.mp4"
+
+    transformation_matrix = get_court_perspective_transform()
+
+    dodgeball_tracker = DodgeballTracker(input_video, output_video, detected_box_objects, transformation_matrix)
+
+    dodgeball_tracker.main()

dodgeballtracker/logic.py

@@ -7,7 +7,7 @@ import cv2
 from dodgeballtracker.helper import create_video_writer, iter_frames
 import matplotlib
 import numpy as np
-from boxmot import DeepOCSORT
+from boxmot import DeepOcSort as DeepOCSORT
 
 
 
@@ -125,19 +125,20 @@ class DodgeballTracker:
 
     def _get_tracker(self):
         return DeepOCSORT(
-            model_weights=Path('lmbn_n_cuhk03_d.pt'),  # which ReID model to use
+            Path('lmbn_n_cuhk03_d.pt'),  # which ReID model to use
-            device=torch.device("mps"),
+            torch.device("cpu"),
-            fp16=True,
+            True,
         )
 
     def _get_detection_model(self):
         """
         load the pre-trained YOLOv8n model
         """
-        return YOLO("yolov8n.pt")
+        return YOLO("yolo11n.pt", verbose=True)
 
     def main(self):
         # define some constants
+        print("started")
 
         video_cap = cv2.VideoCapture(str(self.input_path))
         writer = create_video_writer(video_cap, str(self.output_path))
@@ -150,12 +151,15 @@ class DodgeballTracker:
             # run the YOLO model on the frame
             res = []
             detections = self.run_model_on_frame(model, frame)
+            print("ici?")
             for data in detections.boxes.data.tolist():
+                print("la?")
                 is_good_box = self.plot_boxe_to_frame(data, frame)
                 if is_good_box:
                     res.append(data)
 
             # show the frame to our screen
+            print("tracker?")
             data_ = tracker.update(np.array(res), frame)
             self.print_tracker_data(data_, i, ts)
 
@@ -163,8 +167,10 @@ class DodgeballTracker:
 
             if cv2.waitKey(1) == ord("q"):
                 break
+        print("fini")
 
         video_cap.release()
         writer.release()
         cv2.destroyAllWindows()
         self.persist_points()
+        print("finished")

download-video

@@ -0,0 +1,7 @@
+#!/usr/bin/env bash
+
+yt-dlp --write-info-json \
+       --output data/full.mp4 \
+       'https://www.youtube.com/watch?v=Spu6OlAZHUo'
+
+ffmpeg -ss 00:19:15.00 -i data/full.mp4.webm -t 00:00:30.00 -c copy data/small.mp4

flake.lock

@@ -0,0 +1,130 @@
+{
+  "nodes": {
+    "flake-utils": {
+      "inputs": {
+        "systems": "systems"
+      },
+      "locked": {
+        "lastModified": 1726560853,
+        "narHash": "sha256-X6rJYSESBVr3hBoH0WbKE5KvhPU5bloyZ2L4K60/fPQ=",
+        "owner": "numtide",
+        "repo": "flake-utils",
+        "rev": "c1dfcf08411b08f6b8615f7d8971a2bfa81d5e8a",
+        "type": "github"
+      },
+      "original": {
+        "owner": "numtide",
+        "repo": "flake-utils",
+        "type": "github"
+      }
+    },
+    "flake-utils_2": {
+      "inputs": {
+        "systems": "systems_2"
+      },
+      "locked": {
+        "lastModified": 1726560853,
+        "narHash": "sha256-X6rJYSESBVr3hBoH0WbKE5KvhPU5bloyZ2L4K60/fPQ=",
+        "owner": "numtide",
+        "repo": "flake-utils",
+        "rev": "c1dfcf08411b08f6b8615f7d8971a2bfa81d5e8a",
+        "type": "github"
+      },
+      "original": {
+        "owner": "numtide",
+        "repo": "flake-utils",
+        "type": "github"
+      }
+    },
+    "nixpkgs": {
+      "locked": {
+        "lastModified": 1729595756,
+        "narHash": "sha256-rNaLWDqjgy23Y6M3K/e7Kiyimq04ikDMrErpqgXWcV0=",
+        "owner": "NixOS",
+        "repo": "nixpkgs",
+        "rev": "782740762fb281404740b6b7084d356c3dab1173",
+        "type": "github"
+      },
+      "original": {
+        "owner": "NixOS",
+        "ref": "nixpkgs-unstable",
+        "repo": "nixpkgs",
+        "type": "github"
+      }
+    },
+    "nixpkgs_2": {
+      "locked": {
+        "lastModified": 1729595756,
+        "narHash": "sha256-rNaLWDqjgy23Y6M3K/e7Kiyimq04ikDMrErpqgXWcV0=",
+        "owner": "NixOS",
+        "repo": "nixpkgs",
+        "rev": "782740762fb281404740b6b7084d356c3dab1173",
+        "type": "github"
+      },
+      "original": {
+        "owner": "NixOS",
+        "ref": "nixpkgs-unstable",
+        "repo": "nixpkgs",
+        "type": "github"
+      }
+    },
+    "opencv-python-related": {
+      "inputs": {
+        "flake-utils": "flake-utils_2",
+        "nixpkgs": "nixpkgs_2"
+      },
+      "locked": {
+        "lastModified": 1729677213,
+        "narHash": "sha256-n+g2ROk4ytvZW84+vjaQMarVI/sFoiEUXxMxPnlM9BU=",
+        "owner": "all-dressed-programming",
+        "repo": "opencv-python-related",
+        "rev": "fb816cdf83b7779962c6b8479b377b2927a9ea2d",
+        "type": "gitlab"
+      },
+      "original": {
+        "owner": "all-dressed-programming",
+        "repo": "opencv-python-related",
+        "type": "gitlab"
+      }
+    },
+    "root": {
+      "inputs": {
+        "flake-utils": "flake-utils",
+        "nixpkgs": "nixpkgs",
+        "opencv-python-related": "opencv-python-related"
+      }
+    },
+    "systems": {
+      "locked": {
+        "lastModified": 1681028828,
+        "narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
+        "owner": "nix-systems",
+        "repo": "default",
+        "rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
+        "type": "github"
+      },
+      "original": {
+        "owner": "nix-systems",
+        "repo": "default",
+        "type": "github"
+      }
+    },
+    "systems_2": {
+      "locked": {
+        "lastModified": 1681028828,
+        "narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
+        "owner": "nix-systems",
+        "repo": "default",
+        "rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
+        "type": "github"
+      },
+      "original": {
+        "owner": "nix-systems",
+        "repo": "default",
+        "type": "github"
+      }
+    }
+  },
+  "root": "root",
+  "version": 7
+}

flake.nix

@@ -0,0 +1,25 @@
+{
+  description = "Pre-built CPU-only OpenCV packages for Python.  ";
+  inputs = {
+    nixpkgs.url = "github:NixOS/nixpkgs/nixpkgs-unstable";
+    opencv-python-related.url = "gitlab:all-dressed-programming/opencv-python-related";
+    flake-utils.url = "github:numtide/flake-utils";
+  };
+
+  outputs = { self, nixpkgs, flake-utils, opencv-python-related }:
+    flake-utils.lib.eachDefaultSystem (system:
+      let
+        pkgs = nixpkgs.legacyPackages.${system};
+        pythonPackages = pkgs.python312Packages // opencv-python-related.packages.${system}.python312Packages;
+        virtual-env = pkgs.python312.withPackages (ps: [ ps.matplotlib
+                                                         pythonPackages.opencv4
+                                                         pythonPackages.boxmot
+                                                         pythonPackages.ultralytics ]);
+
+      in {
+        packages = {
+          env = virtual-env;
+        };
+        devShells.default = pkgs.mkShell { buildInputs = [ virtual-env pkgs.yt-dlp pkgs.ffmpeg_7]; };
+      });
+}

visualizer/src/api/mod.tsx

@@ -35,7 +35,7 @@ apiRouter.get("/match/:id/pane/player", async function(ctx){
 });
 
 apiRouter.get("/match/:id/pane/player/data", async function(ctx){
-    ctx.response.body = <svg:rect width="100" height="100" />
+    ctx.response.body = <rect width="100" height="100"/>
 });
 
 apiRouter.get('/list-matches', async (ctx) => {

visualizer/src/api/tab.tsx

@@ -32,7 +32,8 @@ export class ViewTabService {
     playerTab(matchInfo: MatchInfo){
         return (<div>
             <div id="foo"></div>
-            <form hx-get={"/api/v1/match/:id/pane/player/data"}
+            <form hx-swap="innerHTML"
+                  hx-get={"/api/v1/match/:id/pane/player/data"}
                   hx-target="#court-content">
                 <div class="field is-horizontal">
                   <div class="field-label is-normal">

visualizer/src/views/base.tsx

@@ -8,7 +8,7 @@ export function Head(){
     <link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/highlightjs/cdn-release@11.9.0/build/styles/default.min.css"/>
     <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/styles/atom-one-light.min.css"/>
 
-    <script src="https://unpkg.com/htmx.org@1.9.9"></script>
+    <script src="/vendor/htmx/htmx.js"></script>
   </head>)
 }
 

visualizer/src/views/mod.tsx

@@ -19,6 +19,7 @@ function Court(){
         <line x1={600} x2={600} y1={0} y2={450} style={returnLine}></line>,
     ]
     return (<svg class="court-side"
+                 xmlns="http://www.w3.org/2000/svg"
                  style={{width: 900 + 2 * margin, height: 450 + 2 * margin, backgroundColor: 'pink'}}>
         <g class="court-border" id="court" transform = {`translate(${margin} ${margin})`}>
             <rect width={900} height={450} style={courtBorder}/>