Renamed imagemanipv2_mod into imagemanipv2_multi_ops. Added imagemani…

…pv2_all_ops example

examples/python/ImageManip/image_manip_v2_all_ops.py

@@ -0,0 +1,63 @@
+import depthai as dai
+import cv2
+
+# pipeline = dai.Pipeline(dai.Device(dai.DeviceInfo('10.12.103.165')))
+pipeline = dai.Pipeline()
+
+manip_input = pipeline.create(dai.node.ImageManipV2)
+manip_input.initialConfig.setFrameType(dai.ImgFrame.Type.BGR888p)
+inputQueue = manip_input.inputImage.createInputQueue()
+
+manip_ops = [
+    # Resize operations. If aspect ratio isn't the same, the image will be stretched/cropped/letterboxed (depending on resize mode)
+    # Docs here: https://docs.luxonis.com/software/depthai/resolution-techniques/
+    ('resize_stretch', lambda conf: conf.setOutputSize(256, 200, dai.ImageManipConfigV2.ResizeMode.STRETCH)),
+    ('resize_letterbox', lambda conf: conf.setOutputSize(256, 200, dai.ImageManipConfigV2.ResizeMode.LETTERBOX)),
+    ('resize_center_crop', lambda conf: conf.setOutputSize(256, 200, dai.ImageManipConfigV2.ResizeMode.CENTER_CROP)),
+    # Crop the image topLeft (10,40) to bottomRight (310,110)
+    ('crop', lambda conf: conf.addCrop(x=50, y=50, w=150, h=200)),
+    # Flip the frame vertically/horizontally
+    ('flip_vertical', lambda conf: conf.addFlipVertical()),
+    ('flip_horizontal', lambda conf: conf.addFlipHorizontal()),
+    # Scale the image by 0.7x in x and 0.5x in y
+    ('scale', lambda conf: conf.addScale(0.7, 0.5)),
+    # Rotate. If center isn't specified, it will rotate around center (0.5, 0.5)
+    ('rotate_90_deg', lambda conf: conf.addRotateDeg(90)),
+    ('rotate_90_deg_center', lambda conf: conf.addRotateDeg(90, center=dai.Point2f(0.2, 0.3)).setOutputCenter(False)),
+    ('transform_affine', lambda conf: conf.addTransformAffine( # Shearing
+        [1, 0.5,
+         0.2, 1])),
+    ('transform_perspective', lambda conf: conf.addTransformPerspective(
+        [1.0, 0.2, 0.0,  # First row
+        0.1, 1.0, 0.0,  # Second row
+        0.001, 0.002, 1.0])),  # Third row
+    ('frame_type', lambda conf: conf.setFrameType(dai.ImgFrame.Type.RAW8)), # to Grayscale
+]
+
+# Dynamically create ImageManipV2 nodes, apply configurations, and set up queues
+queues = {}
+for name, config in manip_ops:
+    print(name, config)
+    manip = pipeline.create(dai.node.ImageManipV2)
+    config(manip.initialConfig)
+    manip_input.out.link(manip.inputImage)
+    queues[name] = manip.out.createOutputQueue(maxSize=4, blocking=False)
+
+
+imgFrame = dai.ImgFrame()
+
+input_frame = cv2.imread('../models/lenna.png') # 512x512
+# Send 256x256 image to the device
+imgFrame.setCvFrame(cv2.pyrDown(input_frame), dai.ImgFrame.Type.BGR888i)
+inputQueue.send(imgFrame)
+
+cv2.imshow('input_image', input_frame)
+
+
+pipeline.start()
+
+for name, queue in queues.items():
+    inFrame = queue.get()
+    cv2.imshow(name, inFrame.getCvFrame())
+
+key = cv2.waitKey(0)

examples/python/ImageManip/image_manip_v2_mod.py → examples/python/ImageManip/image_manip_v2_multi_ops.py

@@ -13,21 +13,23 @@
 manip.initialConfig.setFrameType(dai.ImgFrame.Type.NV12)
 manip.setMaxOutputFrameSize(2709360)
 
-camOut = camRgb.requestOutput((1920, 1080))
-camOut.link(manip.inputImage)
+camRgb.requestOutput((1920, 1080)).link(manip.inputImage)
+
+out = manip.out.createOutputQueue()
+
+import json
+with open('pipeline.json', 'w') as f:
+    f.write(json.dumps(pipeline.serializeToJson()))
 
-manipQ = manip.out.createOutputQueue()
-camQ = camOut.createOutputQueue()
 
 pipeline.start()
 
 print(manip.initialConfig)
 
 while True:
-    if manipQ.has():
-        cv2.imshow("Manip frame", manipQ.get().getCvFrame())
-    if camQ.has():
-        cv2.imshow("Camera frame", camQ.get().getCvFrame())
-    key = cv2.waitKey(1)
-    if key == ord('q'):
-        break
+    inFrame = out.get()
+    if inFrame is not None:
+        cv2.imshow("Show frame", inFrame.getCvFrame())
+        key = cv2.waitKey(1)
+        if key == ord('q'):
+            break