reverting draw to smaller

create_games/data/game_ideas.json

@@ -1,9 +1,9 @@
 [
     {
-        "Name": "Diagnostic Draw",
-        "Description": "A drawing-based game to illustrate various illnesses",
-        "Rules": "1. Each player takes turns drawing a single thing that represents an illness.\n2. The illness should be common and easily relatable.\n3. Players take turns guessing the illness being drawn.",
-        "Tips": "Can you draw a symbol that represents a headache?",
-        "InitialQuestion": "Draw a simple symbol that represents a cough."
+        "Name": "Blazing Sunburn",
+        "Description": "A drawing-based game where players try to draw a humorous sunburn-related scenario.",
+        "Rules": "1. Each player takes turns to draw a sunburn-related scene or situation.\n2. Players have limited time to complete their drawing.\n3. The drawings should aim to be creative and humorous.",
+        "Tips": "Can you draw a person with funny shaped sunburns? How about an unconventional object getting sunburnt?",
+        "InitialQuestion": "Draw a person with a sunburn that resembles something else."
     }
 ]

home_view/ui_home.py

@@ -144,20 +144,17 @@ with gr.Blocks() as ui:
                 buildPlayLabel= gr.Markdown(constants.BUILDPLAY_LABEL, container=False)    
             with gr.Column():
                 directionsLabel= gr.Markdown(constants.DIRECTIONS_LABEL, container=False)    
-                directions= gr.Markdown(constants.DIRECTIONS, container=False)    
-
+                directions= gr.Markdown(constants.DIRECTIONS, container=False)   
         playersCB = gr.CheckboxGroup ([], label=constants.PLAYERS, info=constants.PLAYERS_INFO )
         gamePlay=gr.Radio(["Draw", "Chat"], label=constants.GAME_TYPE, value="Chat")
         createBtn = gr.Button(value=constants.CREATE_GAME, variant="primary")
-
     with gr.Column(visible=False) as pGame:     
         with gr.Row():
             with gr.Column():
                 chatTitle= gr.Markdown ()        
                 chatDesc= gr.Markdown ()    
                 gameTopic=gr.Markdown() 
-                players=gr.Markdown()               
-              
+                players=gr.Markdown()                             
             with gr.Column():
                 rules=gr.Markdown(constants.RULES_LABEL)
                 chatRules=gr.Markdown(constants.GAME_DESC)        
@@ -168,8 +165,9 @@ with gr.Blocks() as ui:
             drawMD=gr.Markdown()        
             with gr.Column(visible=False) as drawGame:
                 with gr.Row():
-                    sketch=gr.Image(image_mode="L", source="canvas", width=600, height =600, invert_colors=True, interactive=True,
-                                brush_radius=.5, type="numpy", label="Sketch", show_label=True, show_download_button=False) 
+                    sketch=gr.Image(image_mode="L", source="canvas",brush_radius=5, type="pil", shape=(120, 120), 
+                                    invert_colors=True, interactive=True, label="Sketch", 
+                                    show_label=True, show_download_button=False) 
                     label=gr.Label(label="Guesses", show_label=True)
                 resetDrwBtn=gr.Button(value="Reset")
             with gr.Column(visible=False) as chatGame:                 

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:effb6ea6f1593c09e8247944028ed9c309b5ff1cef82ba38b822bee2ca4d0f3c
+size 1656903

requirements.txt

@@ -22,4 +22,6 @@ tiktoken==0.4.0
 torch==2.0.1
 inflect==7.0.0
 Pillow==10.1.0
-streamlit==1.28.0
+streamlit==1.28.0
+gdown==4.7.1
+PySocks==1.7.1

sketch/sketch.py

@@ -3,9 +3,16 @@ from PIL import Image
 import numpy as np
 from torch import nn
 from pathlib import Path
+import gdown
+#PATH="sketch/class_names.txt"
+#LABELS = Path(PATH).read_text().splitlines()
 
-PATH="sketch/class_names.txt"
-LABELS = Path(PATH).read_text().splitlines()
+
+url = 'https://drive.google.com/uc?id=1dsk2JNZLRDjC-0J4wIQX_FcVurPaXaAZ'
+output = 'pytorch_model.bin'
+gdown.download(url, output, quiet=False)
+
+LABELS = Path('sketch/class_names.txt').read_text().splitlines()
 
 model = nn.Sequential(
     nn.Conv2d(1, 32, 3, padding='same'),
@@ -22,11 +29,11 @@ model = nn.Sequential(
     nn.ReLU(),
     nn.Linear(256, len(LABELS)),
 )
-state_dict = torch.load('sketch/pytorch_model.bin',    map_location='cpu')
+state_dict = torch.load('sketch/pytorch_model.bin',map_location='cpu')
 model.load_state_dict(state_dict, strict=False)
 model.eval()
 
-def Predict(img):
+'''def Predict(img):
     if img is None or not img.any():
         print("img is None or empty")
         # Handle the error appropriately
@@ -40,7 +47,6 @@ def Predict(img):
     img_pil = Image.fromarray(img.astype('uint8'))
 
     # Resize the image
-    #img_resized = img_pil.resize((28, 28), Image.ANTIALIAS)
     img_resized = img_pil.resize((28, 28), Image.LANCZOS)
 
     # Convert the PIL image back to a NumPy array
@@ -57,5 +63,22 @@ def Predict(img):
     values, indices = torch.topk(probabilities, 5)
     confidences = {LABELS[i]: v.item() for i, v in zip(indices, values)}
 
-    return confidences
+    return confidences'''
+
+def Predict(im):
+    if im is None:
+        print("img is None or empty")
+        # Handle the error appropriately
+        return
+    im = np.asarray(im.resize((28, 28)))
+        
+    x = torch.tensor(im, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.
+
+    with torch.no_grad():
+        out = model(x)
+
+    probabilities = torch.nn.functional.softmax(out[0], dim=0)
+
+    values, indices = torch.topk(probabilities, 5)
 
+    return {LABELS[i]: v.item() for i, v in zip(indices, values)}