initial commit

README.md

@@ -1,10 +1,10 @@
 ---
-title: RecycleTree
-emoji: 👀
+title: RecycleTree - Trash/Recyclable Classification
+emoji: ♻️
 colorFrom: green
-colorTo: purple
+colorTo: green
 sdk: gradio
-sdk_version: 3.19.1
+sdk_version: 3.9
 app_file: app.py
 pinned: false
 license: openrail

app.py

@@ -0,0 +1,152 @@
+import gradio as gr
+from huggingface_hub import from_pretrained_fastai
+import os
+os.environ["HF_ENDPOINT"] = "https://huggingface.co"
+
+materials_model = from_pretrained_fastai("pyesonekyaw/recycletree_materials")
+paper_model = from_pretrained_fastai("pyesonekyaw/recycletree_paper")
+plastic_model = from_pretrained_fastai("pyesonekyaw/recycletree_plastic")
+metal_model = from_pretrained_fastai("pyesonekyaw/recycletree_metal")
+others_model = from_pretrained_fastai("pyesonekyaw/recycletree_others")
+glass_model = from_pretrained_fastai("pyesonekyaw/recycletree_glass")
+
+examples = ["Examples/1.jpg", "Examples/2.jpg",
+            "Examples/3.jpg", "Examples/4.jpg", "Examples/5.jpg"]
+
+material_names = ['Glass', 'Metal', 'Others', 'Paper', 'Plastic']
+plastic_names = ['CD Disk', 'Straw', 'Plastic Bag', 'Clothes Hanger', 'Plastic Container or Bottle',
+                 'Disposable Cutlery', 'Plastic Packaging', 'Plastic Packaging With Foil', 'Styrofoam']
+paper_names = ['Beverage Carton', 'Cardboard', 'Chopsticks', 'Disposables', 'Paper Bag', 'Paper Packaging',
+               'Paper Product', 'Receipt', 'Paper Roll', 'Paper Sheet', 'Tissue Box', 'Tissue Paper']
+glass_names = ['Ceramic', 'Glassware', 'Lightbulb']
+other_names = ['Battery', 'Electronic Waste', 'Stationery']
+metal_names = ['Aerosol Can', 'Aluminium Foil or Tray', 'Metal Can or Container']
+
+material_num_name_dict = {
+  "metal": "Metal",
+  "glass": "Glass",
+  "paper": "Paper",
+  "plastic": "Plastic",
+  "others": "Others",
+}
+
+plastic_item_num_dict = {
+  "CD Disk": ["Yes", "Nil"],
+  "Straw": ["No, dispose as general waste","Nil"],
+  "Plastic Bag": ["Yes, if they are not oxo- and bio- degradable bags", "Contaminated with food waste/liquid waste/other forms of waste "],
+  "Clothes Hanger": ["Yes", "Made up of more than one plastic, if unsure, just dispose as normal waste "],
+  "Plastic Container or Bottle": ["Yes", "When they are not emptied or not rinsed "],
+  "Disposable Cutlery": ["No, dispose as general waste", "Nil"],
+  "Plastic Packaging": ["Yes, for things like bubble wrap and egg tray but no if directly enclosing food like cling wrap", "Contaminated with food contents "],
+  "Plastic Packaging With Foil": ["No","Nil"],
+  "Styrofoam": ["No, dispose as general waste","Nil"]
+}
+glass_item_num_dict = {
+  "Ceramic": ["No, donate if can be reused", "Nil"],
+  "Glassware": ["Yes","If there is liquid/solid residue inside the glassware "],
+  "Lightbulb": ["Could be recycled at specific collection points which can be found on onemap.sg, under Lighting waste collection points", "Nil"]
+}
+metal_item_num_dict = {
+  "Aerosol Can": ["Yes","If there are any remaining contents in the can"],
+  "Aluminium Foil or Tray": ["Yes","If there is any residue "],
+  "Metal Can or Container": ["Yes","If there is any residue "]
+}
+others_item_num_dict = {
+  "battery": ["Battery","No, rechargeable batteries can be recycled through specific collection points (e-waste collection)", "Nil"],
+  "electronic_waste": ["Electronic Waste","Can be recycled through specific collection points (e-waste collection)"],
+  "stationery": ["Stationery","No, donate if can be reused"]
+}
+paper_item_num_dict = {
+  "Beverage Carton": ["Yes, rinsed and flattened","Nil"],
+  "Cardboard": ["Yes","Remains of other materials such as tape, contaminated with other waste"],
+  "Chopsticks": ["No, dispose as general waste ",],
+  "Disposables": ["No, dispose as general waste ",],
+  "Paper Bag": ["Yes","Contaminated with food waste or other waste "],
+  "Paper Packaging": ["Yes","Made up of more than one material or contaminated with food waste"],
+  "Paper Product": ["Yes","Contaminated with other waste"],
+  "Receipt": ["Yes","Contaminated with other waste"],
+  "Paper Roll": ["Yes","Contaminated with other waste"],
+  "Paper Sheet": ["Yes","Contaminated with other waste "],
+  "Tissue Box": ["Yes","Plastic liners not removed or contaminated with other waste "],
+  "Tissue Paper": ["No, dispose as general waste","Nil"]
+}
+
+
+
+def predict_image(inp):
+    """
+    Performs inference for a given input image and returns the prediction and CAM image.
+    """
+    material_label, material_label_idx, material_probs = materials_model.predict(inp)
+    material_preds = {name: prob for name, prob in zip(material_names, material_probs.tolist())}
+
+    if material_label == 'paper':
+        specific_label, specific_label_idx, specific_probs = paper_model.predict(inp)
+        specific_preds = {name: prob for name, prob in zip(paper_names, specific_probs.tolist())}
+        specific_label = paper_names[int(specific_label_idx)]
+        recyclable_qn = paper_item_num_dict[specific_label][0]
+        recyclable_advice = paper_item_num_dict[specific_label][1]
+
+    elif material_label == 'plastic':
+        specific_label, specific_label_idx, specific_probs = plastic_model.predict(inp)
+        specific_preds = {name: prob for name, prob in zip(plastic_names, specific_probs.tolist())}
+        specific_label = plastic_names[int(specific_label_idx)]
+        recyclable_qn = plastic_item_num_dict[specific_label][0]
+        recyclable_advice = plastic_item_num_dict[specific_label][1]
+
+    elif material_label == 'glass':
+        specific_label, specific_label_idx, specific_probs = glass_model.predict(inp)
+        specific_preds = {name: prob for name, prob in zip(glass_names, specific_probs.tolist())}
+        specific_label = glass_names[int(specific_label_idx)]
+        recyclable_qn = glass_item_num_dict[specific_label][0]
+        recyclable_advice = glass_item_num_dict[specific_label][1]
+
+    elif material_label == 'metal':
+        specific_label, specific_label_idx, specific_probs = metal_model.predict(inp)
+        specific_preds = {name: prob for name, prob in zip(metal_names, specific_probs.tolist())}
+        specific_label = metal_names[int(specific_label_idx)]
+        recyclable_qn = metal_item_num_dict[specific_label][0]
+        recyclable_advice = metal_item_num_dict[specific_label][1]
+
+    elif material_label == 'others':
+        specific_label, specific_label_idx, specific_probs = others_model.predict(inp)
+        specific_preds = {name: prob for name, prob in zip(other_names, specific_probs.tolist())}
+        specific_label = other_names[int(specific_label_idx)]
+        recyclable_qn = others_item_num_dict[specific_label][0]
+        recyclable_advice = others_item_num_dict[specific_label][1]
+
+    return material_preds, specific_preds, recyclable_qn, recyclable_advice
+
+
+with gr.Blocks(title="Trash Classification", css="#custom_header {min-height: 3rem} #custom_title {min-height: 3rem; text-align: center}") as demo:
+    gr.Markdown("# Trash Classification", elem_id="custom_title")
+    gr.Markdown("Gradio Inference interface for classification of trash and recyclables. To use it, simply upload your image, or click one of the examples to load them", elem_id="custom_title")
+
+    with gr.Column():
+        with gr.Column():
+            with gr.Box():
+                gr.Markdown("## Inputs", elem_id="custom_header")
+                input_image = gr.Image(label="Input Image")
+                input_image.style(height=240)
+                btn = gr.Button(value="Submit")
+                btn.style(full_width=True)
+        with gr.Column():
+            with gr.Box():
+                gr.Markdown("## Outputs", elem_id="custom_header")
+                recycling_qn = gr.outputs.Textbox(label="Is this recyclable?")
+                recycling_advice = gr.outputs.Textbox(label="It is not recyclable when:")
+                with gr.Row():
+                    material_probs = gr.outputs.Label(label="Material Prediction")
+                    item_probs = gr.outputs.Label(label="Item Prediction")
+                
+    gr.Examples(
+        examples=examples,
+        inputs=input_image,
+        fn=predict_image,
+        cache_examples=False,
+    )
+
+    btn.click(predict_image, inputs=[input_image],
+              outputs=[material_probs, item_probs, recycling_qn, recycling_advice])
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,2 @@
+gradio 
+huggingface_hub