From 7b32a55b82388c895a315d9d22d145dc42bb5bca Mon Sep 17 00:00:00 2001 From: Yuantao Feng Date: Sun, 4 Dec 2022 21:37:39 +0800 Subject: [PATCH] Merge pull request #111 from remove-YoloX-dot-py Delete YoloX.py (#111): - Remove the legacy to save git conflicts --- models/object_detection_yolox/YoloX.py | 89 -------------------------- 1 file changed, 89 deletions(-) delete mode 100644 models/object_detection_yolox/YoloX.py diff --git a/models/object_detection_yolox/YoloX.py b/models/object_detection_yolox/YoloX.py deleted file mode 100644 index 0140f20..0000000 --- a/models/object_detection_yolox/YoloX.py +++ /dev/null @@ -1,89 +0,0 @@ -import numpy as np -import cv2 - -class YoloX: - def __init__(self, modelPath, confThreshold=0.35, nmsThreshold=0.5, objThreshold=0.5, backendId=0, targetId=0): - self.num_classes = 80 - self.net = cv2.dnn.readNet(modelPath) - self.input_size = (640, 640) - self.mean = np.array([0.485, 0.456, 0.406], dtype=np.float32).reshape(1, 1, 3) - self.std = np.array([0.229, 0.224, 0.225], dtype=np.float32).reshape(1, 1, 3) - self.strides = [8, 16, 32] - self.confThreshold = confThreshold - self.nmsThreshold = nmsThreshold - self.objThreshold = objThreshold - self.backendId = backendId - self.targetId = targetId - self.net.setPreferableBackend(self.backendId) - self.net.setPreferableTarget(self.targetId) - - self.generateAnchors() - - @property - def name(self): - return self.__class__.__name__ - - def setBackend(self, backenId): - self.backendId = backendId - self.net.setPreferableBackend(self.backendId) - - def setTarget(self, targetId): - self.targetId = targetId - self.net.setPreferableTarget(self.targetId) - - def preprocess(self, img): - blob = np.transpose(img, (2, 0, 1)) - return blob[np.newaxis, :, :, :] - - def infer(self, srcimg): - input_blob = self.preprocess(srcimg) - - self.net.setInput(input_blob) - outs = self.net.forward(self.net.getUnconnectedOutLayersNames()) - - predictions = self.postprocess(outs[0]) - return predictions - - def postprocess(self, outputs): - dets = outputs[0] - - dets[:, :2] = (dets[:, :2] + self.grids) * self.expanded_strides - dets[:, 2:4] = np.exp(dets[:, 2:4]) * self.expanded_strides - - # get boxes - boxes = dets[:, :4] - boxes_xyxy = np.ones_like(boxes) - boxes_xyxy[:, 0] = boxes[:, 0] - boxes[:, 2] / 2. - boxes_xyxy[:, 1] = boxes[:, 1] - boxes[:, 3] / 2. - boxes_xyxy[:, 2] = boxes[:, 0] + boxes[:, 2] / 2. - boxes_xyxy[:, 3] = boxes[:, 1] + boxes[:, 3] / 2. - - # get scores and class indices - scores = dets[:, 4:5] * dets[:, 5:] - max_scores = np.amax(scores, axis=1) - max_scores_idx = np.argmax(scores, axis=1) - - # batched-nms, TODO: replace with cv2.dnn.NMSBoxesBatched when OpenCV 4.7.0 is released - max_coord = boxes_xyxy.max() - offsets = max_scores_idx * (max_coord + 1) - boxes_for_nms = boxes_xyxy + offsets[:, None] - keep = cv2.dnn.NMSBoxes(boxes_for_nms.tolist(), max_scores.tolist(), self.confThreshold, self.nmsThreshold) - - candidates = np.concatenate([boxes_xyxy, max_scores[:, None], max_scores_idx[:, None]], axis=1) - return candidates[keep] - - def generateAnchors(self): - self.grids = [] - self.expanded_strides = [] - hsizes = [self.input_size[0] // stride for stride in self.strides] - wsizes = [self.input_size[1] // stride for stride in self.strides] - - for hsize, wsize, stride in zip(hsizes, wsizes, self.strides): - xv, yv = np.meshgrid(np.arange(hsize), np.arange(wsize)) - grid = np.stack((xv, yv), 2).reshape(1, -1, 2) - self.grids.append(grid) - shape = grid.shape[:2] - self.expanded_strides.append(np.full((*shape, 1), stride)) - - self.grids = np.concatenate(self.grids, 1) - self.expanded_strides = np.concatenate(self.expanded_strides, 1) -- GitLab