From 07deb65a627d168e0cf9e62ec316bf1dbfbca165 Mon Sep 17 00:00:00 2001 From: hehonglu123 Date: Wed, 24 Jul 2024 14:08:39 -0400 Subject: [PATCH] add in yolo training --- pyproject.toml | 5 +- src/flir_toolbox/flir_toolbox.py | 55 ++++++++++++++ src/flir_toolbox/tip_wire.pt | Bin 0 -> 6259635 bytes src/{torch_tracking => flir_toolbox}/torch.pt | Bin yolov8/data_gen_tip.py | 32 ++++++++ yolov8/data_gen_torch.py | 37 +++++++++ yolov8/data_gen_wire.py | 34 +++++++++ .../datasets/tip_wire_yolov8_data/data.yaml | 13 ++++ ...ng.rf.371c32f27019ceeceaa662cd92d05a15.jpg | Bin 0 -> 3303 bytes ...ng.rf.3b0a9d8625ea0ca494e5c1a5b9f90949.jpg | Bin 0 -> 3715 bytes ...ng.rf.5db3dcbdbce094ae22d0be0ec973e5ea.jpg | Bin 0 -> 3518 bytes ...ng.rf.977c2934d49cb7080218c9f2f437dcf3.jpg | Bin 0 -> 3640 bytes ...ng.rf.0fa475dac56d821ca001a7f2cfa35fa9.jpg | Bin 0 -> 3934 bytes ...ng.rf.3e7913352436af11b5e41f787555825b.jpg | Bin 0 -> 3730 bytes ...ng.rf.96e833e30b1e9699f9e3677d312652d0.jpg | Bin 0 -> 3854 bytes 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a/pyproject.toml b/pyproject.toml index 2d5ec9a..a6dd3b4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,14 +8,13 @@ version = "0.1.0" description = "FLIR WAAM Helper Functions." packages = [ - { include = "flir_toolbox", from = "src" }, - { include = "torch_tracking", from = "src" } + { include = "flir_toolbox", from = "src" } ] authors = ["Honglu He ",] maintainers = ["Honglu He ",] -include = ["CHANGELOG.md", "LICENSE", "py.typed","torch_tracking/torch.pt"] +include = ["CHANGELOG.md", "LICENSE", "py.typed"] license = "BSD-3-Clause" readme = "README.md" diff --git a/src/flir_toolbox/flir_toolbox.py b/src/flir_toolbox/flir_toolbox.py index 17d3c49..c54f699 100644 --- a/src/flir_toolbox/flir_toolbox.py +++ b/src/flir_toolbox/flir_toolbox.py @@ -179,6 +179,15 @@ def weld_detection_steel(raw_img,yolo_model,threshold=1.5e4,area_threshold=50,pe return centroid, bbox, torch_centroid, torch_bbox +def weld_detection_steel(raw_img,torch_model,tip_model): + + ## Torch detection + torch_centroid, torch_bbox=torch_detect_yolo(raw_img,torch_model) + ## Tip detection + tip_centroid, tip_bbox=tip_wire_detect_yolo(raw_img,tip_model) + + return tip_centroid, tip_bbox, torch_centroid, torch_bbox + def torch_detect(ir_image,template,template_threshold=0.3,pixel_threshold=1e4): ###template matching for torch, return the upper left corner of the matched region @@ -217,6 +226,25 @@ def torch_detect_yolo(ir_image,yolo_model,pixel_threshold=1e4,percentage_thresho #run yolo result= yolo_model.predict(ir_torch_tracking,verbose=False, conf=0.5)[0] + conf_all = result.boxes.conf.cpu().numpy() #find the most confident torch prediction + if len(conf_all)>0: + max_conf_idx=np.argmax(conf_all) + bbox = result.boxes.cpu().xyxy[max_conf_idx].numpy()\ + #change bbox to opencv format + bbox[2]=bbox[2]-bbox[0] + bbox[3]=bbox[3]-bbox[1] + centroid = np.array([(bbox[0]+bbox[2])/2,(bbox[1]+bbox[3])/2]) + return centroid, bbox.astype(int) + else: + return None, None + +def tip_detect_yolo(ir_image,tip_model): + ir_tip_tracking=copy.deepcopy(ir_image) + ir_tip_tracking = ((ir_tip_tracking - np.min(ir_tip_tracking)) / (np.max(ir_tip_tracking) - np.min(ir_tip_tracking))) * 255 + ir_tip_tracking = ir_tip_tracking.astype(np.uint8) + ir_tip_tracking = cv2.cvtColor(ir_tip_tracking, cv2.COLOR_GRAY2BGR) + #run yolo + result= tip_model.predict(ir_tip_tracking,verbose=False)[0] if result.boxes.cls.cpu().numpy()==0: bbox = result.boxes.cpu().xyxy[0].numpy()\ #change bbox to opencv format @@ -227,6 +255,33 @@ def torch_detect_yolo(ir_image,yolo_model,pixel_threshold=1e4,percentage_thresho else: return None, None +def tip_wire_detect_yolo(ir_image,tip_wire_model): + ir_tip_wire_tracking=copy.deepcopy(ir_image) + pixel_threshold=0.77*np.max(ir_tip_wire_tracking) + ir_tip_wire_tracking[ir_tip_wire_tracking>pixel_threshold]=pixel_threshold + ir_tip_wire_tracking = ((ir_tip_wire_tracking - np.min(ir_tip_wire_tracking)) / (np.max(ir_tip_wire_tracking) - np.min(ir_tip_wire_tracking))) * 255 + ir_tip_wire_tracking = ir_tip_wire_tracking.astype(np.uint8) + ir_tip_wire_tracking = cv2.cvtColor(ir_tip_wire_tracking, cv2.COLOR_GRAY2BGR) + #run yolo + result= tip_wire_model.predict(ir_tip_wire_tracking,verbose=False,conf=0.5)[0] + cls_list = result.boxes.cls.cpu().numpy().astype(int) + counts = np.bincount(cls_list) + # Check if there is exactly one 0 and one 1 + if len(counts) >= 2 and counts[0] == 1 and counts[1] == 1: + idx0=np.where(cls_list==0)[0][0] + idx1=np.where(cls_list==1)[0][0] + #get the lower right corner of the bounding box of cls 0 + x0_left,y0_left,x1_left,y1_left = result.boxes.cpu().xyxy[idx0].numpy() + #get the lower left corner of the bounding box of cls 1 + x0_right,y0_right,x1_right,y1_right = result.boxes.cpu().xyxy[idx1].numpy() + #get the average of the two points + centroid_x = (x1_left+x0_right)/2 + centroid_y = (y1_left+y1_right)/2 + + return np.array([centroid_x,centroid_y]), (int(centroid_x - 1.5), int(centroid_y - 1.5), 3, 3) + + return None, None + def get_pixel_value(ir_image,coord,window_size): ###get pixel value larger than avg within the window window = ir_image[coord[1]-window_size//2:coord[1]+window_size//2+1,coord[0]-window_size//2:coord[0]+window_size//2+1] diff --git a/src/flir_toolbox/tip_wire.pt b/src/flir_toolbox/tip_wire.pt new file mode 100644 index 0000000000000000000000000000000000000000..469bd5ff42f5b7ea9d1cf754a2aaba1c0c9ada23 GIT binary patch literal 6259635 zcmb511%MRC*0u?8V#GZmPK>|;%MvA?4I$Doq6As85MY_J4be%6OeXH`dgJacH}3B4 z?ympy)~TuO>~O!IgnLgv=Tvu9P1UJ)dwP0$wj4bD3|+d+GE0}b|GIaXr^|2~**a!& z%W9*B=fitV++*BE>&@9^$AA1crE9s=rRPxU=)z7drRjz)0ygw+=(lR`0joCj*``n5 z)f@V*-nVzJeoeg_8wZxU4xO1DCbwAon6?R}>4(mQ*VL<_SO0#c8A8#xF(X?hw6~OI z9J&%k>u$W|W~=t?)w@T});yoszWQpbO&XWm@Ns+RV@9_38re2}wYdL^rJ1}JZ6n)D zGY?&iV{1o@BGjwXVWnAy&d4q;6Wd0%mS)}bZ~hxPJAn}`?fJ0LWAX_t?d_#*n}?mo zw~cBUSDI~Pv5E;3dga60_h|37K}+5;GUv4n(O%t3v#)qyX^wJf&YnXxrgU}8gfSC# 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