diff --git a/examples/opencv/.gitignore b/examples/opencv/.gitignore
index 152ee41c6..68150b65f 100644
--- a/examples/opencv/.gitignore
+++ b/examples/opencv/.gitignore
@@ -1,3 +1,4 @@
 # pixi environments
 .pixi
 haarcascade_frontalface_default.xml
+*.png
diff --git a/examples/opencv/README.md b/examples/opencv/README.md
new file mode 100644
index 000000000..40b282fbd
--- /dev/null
+++ b/examples/opencv/README.md
@@ -0,0 +1,29 @@
+# OpenCV example
+OpenCV is a powerfull tool to do computer vision and fully opensource.
+
+Here are some example on how to use it with `pixi`.
+
+## Simple face detection algorithm
+```shell
+pixi run start
+```
+![Face detection result](https://github.com/ruben-arts/pixi/assets/12893423/c0151496-caae-407c-9e90-0f71f3c19aa7)
+
+
+## Simple camera calibration script
+```shell
+pixi run calibrate
+```
+
+You'll need a checkerboard for this to work.
+Print this: [![chessboard](https://github.com/opencv/opencv/blob/4.x/doc/pattern.png?raw=true)](https://github.com/opencv/opencv/blob/4.x/doc/pattern.png)
+
+To make a picture for calibration press `SPACE`
+Do this approximately 10 times with the chessboard in view of the camera
+
+After that press `ESC` which will start the calibration.
+
+When the calibration is done the camera will be used again to find the distance to the checkerboard.
+
+![callibrated camera result](https://github.com/ruben-arts/pixi/assets/12893423/f42825d7-5010-4805-9f6b-b02075395413)
+
diff --git a/examples/opencv/calibrate.py b/examples/opencv/calibrate.py
new file mode 100644
index 000000000..525102653
--- /dev/null
+++ b/examples/opencv/calibrate.py
@@ -0,0 +1,132 @@
+import cv2
+import numpy as np
+
+# Termination criteria
+criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 0.001)
+
+# Prepare object points
+# The example chessboard is 9x6.
+CHESSBOARD_X = 6
+CHESSBOARD_Y = 9
+# The example chessboard printed on a A4 paper will approximaly be 24mm in width and height.
+SQUARE_SIZE_MM = 22.5
+
+objp = np.zeros((CHESSBOARD_X * CHESSBOARD_Y, 3), np.float32)
+objp[:,:2] = np.mgrid[0:CHESSBOARD_Y, 0:CHESSBOARD_X].T.reshape(-1, 2) * (SQUARE_SIZE_MM * 0.001)
+
+# Arrays to store object points and image points
+objpoints = []
+imgpoints = []
+
+# Initialize the camera
+cap = cv2.VideoCapture(0)
+
+# Set the frame width and height
+cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
+cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
+
+img_counter = 0
+
+print("Press SPACE to capture an image for calibration.")
+print("Press ESC to calibrate the camera using the previously captured images.")
+
+while True:
+    ret, frame = cap.read()
+    if not ret:
+        break
+
+    frame_clean = cv2.copyTo(frame, None)
+    # Find the chess board corners
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    ret, corners = cv2.findChessboardCorners(gray, (CHESSBOARD_Y, CHESSBOARD_X), None)
+
+    if ret:
+        cv2.drawChessboardCorners(frame, (CHESSBOARD_Y, CHESSBOARD_X), corners, ret)
+
+    cv2.imshow("Test", frame)
+    k = cv2.waitKey(1)
+
+    if k%256 == 27:
+        # ESC pressed
+        print("Escape hit, closing...")
+        break
+    elif k%256 == 32:
+        # SPACE pressed
+        img_name = "opencv_frame_{}.png".format(img_counter)
+        cv2.imwrite(img_name, frame_clean)
+        print("{} written!".format(img_name))
+        img_counter += 1
+
+        # Convert to grayscale
+        gray = cv2.cvtColor(frame_clean, cv2.COLOR_BGR2GRAY)
+
+        # Find the chess board corners
+        ret, corners = cv2.findChessboardCorners(gray, (CHESSBOARD_Y, CHESSBOARD_X), None)
+
+        # If found, add object points, image points (after refining them)
+        if ret:
+            objpoints.append(objp)
+
+            corners2 = cv2.cornerSubPix(gray, corners, (11,11), (-1,-1), criteria)
+            imgpoints.append(corners2)
+        else:
+            print("No chessboard detected in this image: {img_name}")
+
+cv2.destroyAllWindows()
+
+if len(objpoints) > 0:
+    # Perform camera calibration
+    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)
+
+    # Print out the camera calibration results
+    print("Camera matrix : \n")
+    print(mtx)
+    print("dist : \n")
+    print(dist)
+    print("rvecs : \n")
+    print(rvecs)
+    print("tvecs : \n")
+    print(tvecs)
+
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+        k = cv2.waitKey(1)
+
+        if k%256 == 27:
+            # ESC pressed
+            print("Escape hit, closing...")
+            break
+
+        # Convert to grayscale
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+        # Find the chess board corners
+        ret, corners = cv2.findChessboardCorners(gray, (CHESSBOARD_Y, CHESSBOARD_X), None)
+
+        if ret:
+            corners2 = cv2.cornerSubPix(gray, corners, (11,11), (-1,-1), criteria)
+            imgpoints.append(corners2)
+
+            # Draw and display the corners
+            frame = cv2.drawChessboardCorners(frame, (CHESSBOARD_Y, CHESSBOARD_X), corners2, ret)
+
+            # Estimate pose of pattern
+            _, rvecs, tvecs, _ = cv2.solvePnPRansac(objp, corners2, mtx, dist)
+
+            # Compute distance from camera to pattern
+            x_distance = tvecs[0][0]
+            y_distance = tvecs[1][0]
+            z_distance = tvecs[2][0]
+
+            text = f"X: {x_distance:.2f}m, Y: {y_distance:.2f}m, Z: {z_distance:.2f}m"
+            cv2.putText(frame, text, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2, cv2.LINE_AA)
+
+        cv2.imshow('Result', frame)
+
+else:
+    print("Not enough images where corners were found. Please capture more images.")
+
+cap.release()
+cv2.destroyAllWindows()
diff --git a/examples/opencv/pixi.lock b/examples/opencv/pixi.lock
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+    brotli-bin: ==1.0.9 hb7f2c08_8
+    libbrotlidec: ==1.0.9 hb7f2c08_8
+  url: https://conda.anaconda.org/conda-forge/osx-64/brotli-1.0.9-hb7f2c08_8.tar.bz2
   hash:
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   category: main
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-  build: h912dcd9_0
-- name: krb5
-  version: 1.20.1
+  build: hb7f2c08_8
+- name: brotli-bin
+  version: 1.0.9
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/krb5-1.20.1-h69eda48_0.conda
+    libbrotlienc: ==1.0.9 hb7f2c08_8
+    libbrotlidec: ==1.0.9 hb7f2c08_8
+  url: https://conda.anaconda.org/conda-forge/osx-64/brotli-bin-1.0.9-hb7f2c08_8.tar.bz2
   hash:
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   optional: false
   category: main
   source: null
-  build: h69eda48_0
-- name: libnghttp2
-  version: 1.52.0
+  build: hb7f2c08_8
+- name: libbrotlidec
+  version: 1.0.9
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    libev: '>=4.33,<4.34.0a0'
-    openssl: '>=3.0.8,<4.0a0'
-    libzlib: '>=1.2.13,<1.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libnghttp2-1.52.0-hae82a92_0.conda
+    libbrotlicommon: ==1.0.9 hb7f2c08_8
+  url: https://conda.anaconda.org/conda-forge/osx-64/libbrotlidec-1.0.9-hb7f2c08_8.tar.bz2
   hash:
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+    sha256: 52d8e8929b2476cf13fd397d88cefd911f805de00e77090fdc50b8fb11c372ca
   optional: false
   category: main
   source: null
-  build: hae82a92_0
-- name: libedit
-  version: 3.1.20191231
+  build: hb7f2c08_8
+- name: libbrotlienc
+  version: 1.0.9
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    ncurses: '>=6.2,<7.0.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libedit-3.1.20191231-hc8eb9b7_2.tar.bz2
+    libbrotlicommon: ==1.0.9 hb7f2c08_8
+  url: https://conda.anaconda.org/conda-forge/osx-64/libbrotlienc-1.0.9-hb7f2c08_8.tar.bz2
   hash:
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   optional: false
   category: main
   source: null
-  build: hc8eb9b7_2
-- name: libaec
-  version: 1.0.6
+  build: hb7f2c08_8
+- name: libbrotlicommon
+  version: 1.0.9
   manager: conda
-  platform: osx-arm64
-  dependencies:
-    libcxx: '>=14.0.6'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libaec-1.0.6-hb7217d7_1.conda
+  platform: osx-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/libbrotlicommon-1.0.9-hb7f2c08_8.tar.bz2
   hash:
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   optional: false
   category: main
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-  build: hb7217d7_1
+  build: hb7f2c08_8
 - name: c-ares
   version: 1.19.1
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/c-ares-1.19.1-hb547adb_0.conda
+  url: https://conda.anaconda.org/conda-forge/osx-64/c-ares-1.19.1-h0dc2134_0.conda
   hash:
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   optional: false
   category: main
   source: null
-  build: hb547adb_0
+  build: h0dc2134_0
 - name: libev
   version: '4.33'
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libev-4.33-h642e427_1.tar.bz2
+  url: https://conda.anaconda.org/conda-forge/osx-64/libev-4.33-haf1e3a3_1.tar.bz2
   hash:
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   optional: false
   category: main
   source: null
-  build: h642e427_1
+  build: haf1e3a3_1
 - name: libssh2
   version: 1.11.0
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    openssl: '>=3.1.1,<4.0a0'
     libzlib: '>=1.2.13,<1.3.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libssh2-1.11.0-h7a5bd25_0.conda
+    openssl: '>=3.1.1,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libssh2-1.11.0-hd019ec5_0.conda
   hash:
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-    sha256: bb57d0c53289721fff1eeb3103a1c6a988178e88d8a8f4345b0b91a35f0e0015
+    md5: ca3a72efba692c59a90d4b9fc0dfe774
+    sha256: f3886763b88f4b24265db6036535ef77b7b77ce91b1cbe588c0fbdd861eec515
   optional: false
   category: main
   source: null
-  build: h7a5bd25_0
-- name: bzip2
-  version: 1.0.8
+  build: hd019ec5_0
+- name: graphite2
+  version: 1.3.13
   manager: conda
-  platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-h3422bc3_4.tar.bz2
+  platform: osx-64
+  dependencies:
+    libcxx: '>=10.0.1'
+  url: https://conda.anaconda.org/conda-forge/osx-64/graphite2-1.3.13-h2e338ed_1001.tar.bz2
   hash:
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   optional: false
   category: main
   source: null
-  build: h3422bc3_4
+  build: h2e338ed_1001
 - name: libgfortran
   version: 5.0.0
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
     libgfortran5: '*'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libgfortran-5.0.0-12_2_0_hd922786_31.conda
+  url: https://conda.anaconda.org/conda-forge/osx-64/libgfortran-5.0.0-11_3_0_h97931a8_31.conda
   hash:
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-    sha256: 1abde945c2c7377aec9f2f648d9cc1fcb5f818a1e0caf53f8188b1182cbc1332
+    md5: 97451338600bd9c5b535eb224ef6c471
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   optional: false
   category: main
   source: null
-  build: 12_2_0_hd922786_31
+  build: 11_3_0_h97931a8_31
+- name: bzip2
+  version: 1.0.8
+  manager: conda
+  platform: osx-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/bzip2-1.0.8-h0d85af4_4.tar.bz2
+  hash:
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+    sha256: 60ba4c64f5d0afca0d283c7addba577d3e2efc0db86002808dadb0498661b2f2
+  optional: false
+  category: main
+  source: null
+  build: h0d85af4_4
+- name: libedit
+  version: 3.1.20191231
+  manager: conda
+  platform: osx-64
+  dependencies:
+    ncurses: '>=6.2,<7.0.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libedit-3.1.20191231-h0678c8f_2.tar.bz2
+  hash:
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+    sha256: dbd3c3f2eca1d21c52e4c03b21930bbce414c4592f8ce805801575b9e9256095
+  optional: false
+  category: main
+  source: null
+  build: h0678c8f_2
+- name: libunistring
+  version: 0.9.10
+  manager: conda
+  platform: osx-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/libunistring-0.9.10-h0d85af4_0.tar.bz2
+  hash:
+    md5: 40f27dc16f73256d7b93e53c4f03d92f
+    sha256: c5805a58cd2b211bffdc8b7cdeba9af3cee456196ab52ab9a30e0353bc95beb7
+  optional: false
+  category: main
+  source: null
+  build: h0d85af4_0
+- name: fribidi
+  version: 1.0.10
+  manager: conda
+  platform: osx-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/fribidi-1.0.10-hbcb3906_0.tar.bz2
+  hash:
+    md5: f1c6b41e0f56998ecd9a3e210faa1dc0
+    sha256: 4f6db86ecc4984cd4ac88ca52030726c3cfd11a64dfb15c8602025ee3001a2b5
+  optional: false
+  category: main
+  source: null
+  build: hbcb3906_0
 version: 1
diff --git a/examples/opencv/pixi.toml b/examples/opencv/pixi.toml
index e048aa71c..bead7f6b8 100644
--- a/examples/opencv/pixi.toml
+++ b/examples/opencv/pixi.toml
@@ -8,6 +8,7 @@ platforms = ["linux-64", "win-64", "osx-64", "osx-arm64"]
 
 [commands]
 start = "python webcam_capture.py"
+calibrate = "python calibrate.py"
 
 [dependencies]
 opencv = "*"