update reqs

PIFu/apps/eval_spaces.py

@@ -18,8 +18,6 @@ from lib.model import *
 
 from PIL import Image
 import torchvision.transforms as transforms
-import glob
-import tqdm
 
 import trimesh
 from datetime import datetime
@@ -124,7 +122,7 @@ if __name__ == '__main__':
         time = datetime.now()
         print("evaluating" , time)
         data = evaluator.load_image(test_image_path, test_mask_path)
-        evaluator.eval(data, True)
+        evaluator.eval(data, False)
         print("done evaluating" , datetime.now() - time)
     except Exception as e:
         print("error:", e.args)

PIFu/requirements.txt

@@ -1,24 +1,23 @@
-cudatoolkit=10.1
 cycler==0.10.0
 decorator==4.4.1
 imageio==2.8.0
 kiwisolver==1.1.0
 matplotlib==3.1.3
 networkx==2.4
-numpy==1.18.1
-opencv-python==4.2.0.32
+numpy==1.21.6
+opencv-python==4.1.2.30
 pathlib==1.0.1
-Pillow==9.0.0
-PyOpenGL==3.1.5
+Pillow==9.1.0
+PyOpenGL==3.1.6
 pyparsing==2.4.6
 python-dateutil==2.8.1
 PyWavelets==1.1.1
-scikit-image==0.16.2
+scikit-image==0.18.3
+scikit-learn==1.0.2
 scipy==1.4.1
 Shapely==1.7.0
 six==1.14.0
 torch==1.4.0
 torchvision==0.5.0
-tqdm==4.43.0
 trimesh==3.5.23
-xxhash==1.4.3
+tqdm==4.64.0

app.py

@@ -1,9 +1,9 @@
 import os
-try: 
+try:
     os.system("pip install --upgrade  torch==1.11.0+cu113 torchvision==0.12.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html")
 except Exception as e:
     print(e)
-    
+
 from pydoc import describe
 from huggingface_hub import hf_hub_download
 import gradio as gr
@@ -12,11 +12,17 @@ import os
 import datetime
 from PIL import Image
 from remove_bg import RemoveBackground
-import torch
+import torch, torchvision, skimage 
+
+print(
+    "torch: ", torch.__version__,
+    "\ntorchvision: ",torchvision.__version__,
+    "\nskimage:", skimage.__version__
+)
 
 net_C = hf_hub_download("radames/PIFu-upright-standing", filename="net_C")
 net_G = hf_hub_download("radames/PIFu-upright-standing", filename="net_G")
-torch.hub.load('pytorch/vision:v0.6.0', 'deeplabv3_resnet101', pretrained=True)
+torch.hub.load('pytorch/vision:v0.10.0', 'deeplabv3_resnet101', pretrained=True)
 
 remove_bg = RemoveBackground()
 
@@ -32,11 +38,18 @@ def process(img_path):
     base = os.path.basename(img_path)
     img_name = os.path.splitext(base)[0]
     print("image name", img_name)
-    img = Image.open(img_path)
+    img_raw = Image.open(img_path)
+    img = img_raw.resize(
+        (800, int(800 * img_raw.size[1] / img_raw.size[0])),
+        Image.Resampling.LANCZOS)
+
     # remove background
     print("Removeing background")
-    foreground = Image.fromarray(remove_bg.inference(img), 'RGBA')
-    foreground.save("./PIFu/inputs/" + img_name + ".png")
+    try: 
+        foreground = Image.fromarray(remove_bg.inference(img), 'RGBA')
+        foreground.save("./PIFu/inputs/" + img_name + ".png")
+    except Exception as e:
+        print(e)
     print("Aliging mask with input training image")
     subprocess.Popen(["python", "./apps/crop_img.py", "--input_image",
                       f'./inputs/{img_name}.png', "--out_path", "./inputs"], cwd="PIFu").communicate()
@@ -84,12 +97,12 @@ The pre-trained model has the following warning:
 iface = gr.Interface(
     fn=process,
     description=description,
-    inputs=gr.Image(type="filepath", label="Input"),
-    outputs=gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0]),
+    inputs=gr.Image(type="filepath", label="Input Image"),
+    outputs=gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0],  label="3D Model"),
     examples=examples,
     allow_flagging="never",
     cache_examples=True
 )
 
 if __name__ == "__main__":
-    iface.launch(debug=True, enable_queue=True)
+    iface.launch(debug=True, enable_queue=False)

remove_bg.py

@@ -6,7 +6,7 @@ from torchvision import transforms
 
 class RemoveBackground(object):
     def __init__(self):
-        self.model = torch.hub.load('pytorch/vision:v0.6.0', 'deeplabv3_resnet101', pretrained=True)
+        self.model = torch.hub.load('pytorch/vision:v0.10.0', 'deeplabv3_resnet101', pretrained=True)
         self.model.eval()
 
     def make_transparent_foreground(self, pic, mask):

requirements.txt

@@ -4,19 +4,19 @@ imageio==2.8.0
 kiwisolver==1.1.0
 matplotlib==3.1.3
 networkx==2.4
-numpy==1.18.1
-opencv-python==4.2.0.32
-Pillow==9.0.0
-PyOpenGL==3.1.5
+numpy==1.21.6
+opencv-python==4.1.2.30
+Pillow==9.1.0
+PyOpenGL==3.1.6
 pyparsing==2.4.6
 python-dateutil==2.8.1
 PyWavelets==1.1.1
-scikit-image
+scikit-image==0.18.3
+scikit-learn==1.0.2
 scipy==1.4.1
 Shapely==1.7.0
 six==1.14.0
-tqdm==4.43.0
+torch==1.4.0
+torchvision==0.5.0
 trimesh==3.5.23
-xxhash==1.4.3
-torch==1.11
-torchvision==0.12.0
+tqdm==4.64.0